Dendritic trafficking faces physiologically critical speed-precision tradeoffs

Understanding molecular signaling cascades in neural disease using multi-resolution models

If the genome defines the program for the operations of a cell, signaling networks execute it. These cascades of chemical, cell-biological, structural, and trafficking events span milliseconds (e.g., synaptic release) to potentially a lifetime (e.g., stabilization of dendritic spines). In principle almost every aspect of neuronal function, particularly at the synapse, depends on signaling. Thus dysfunction of these cascades, whether through mutations, local dysregulation, or infection, leads to disease. The sheer complexity of these pathways is matched by the range of diseases and the diversity of their phenotypes. In this review, we discuss how to build computational models, how these models are essential to tackle this complexity, and the benefits of using families of models at different levels of detail to understand signaling in health and disease.

Topology recapitulates morphogenesis of neuronal dendrites

Branching allows neurons to make synaptic contacts with large numbers of other neurons, facilitating the high connectivity of nervous systems. Neuronal arbors have geometric properties such as branch lengths and diameters that are optimal in that they maximize signaling speeds while minimizing construction costs. In this work, we asked whether neuronal arbors have topological properties that may also optimize their growth or function. We discovered that for a wide range of invertebrate and vertebrate neurons the distributions of their subtree sizes follow power laws, implying that they are scale invariant. The power-law exponent distinguishes different neuronal cell types. Postsynaptic spines and branchlets perturb scale invariance. Through simulations, we show that the subtree-size distribution depends on the symmetry of the branching rules governing arbor growth and that optimal morphologies are scale invariant. Thus, the subtree-size distribution is a topological property that recapitulates the functional morphology of dendrites.

Endoplasmic reticulum network heterogeneity guides diffusive transport and kinetics

The endoplasmic reticulum (ER) is a dynamic network of interconnected sheets and tubules that orchestrates the distribution of lipids, ions, and proteins throughout the cell. The impact of its complex, dynamic morphology on its function as an intracellular transport hub remains poorly understood. To elucidate the functional consequences of ER network structure and dynamics, we quantify how the heterogeneity of the peripheral ER in COS7 cells affects diffusive protein transport. In vivo imaging of photoactivated ER membrane proteins demonstrates their nonuniform spreading to adjacent regions, in a manner consistent with simulations of diffusing particles on extracted network structures. Using a minimal network model to represent tubule rearrangements, we demonstrate that ER network dynamics are sufficiently slow to have little effect on diffusive protein transport. Furthermore, stochastic simulations reveal a novel consequence of ER network heterogeneity: the existence of "hot spots" where sparse diffusive reactants are more likely to find one another. ER exit sites, specialized domains regulating cargo export from the ER, are shown to be disproportionately located in highly accessible regions, further from the outer boundary of the cell. Combining in vivo experiments with analytic calculations, quantitative image analysis, and computational modeling, we demonstrate how structure guides diffusive protein transport and reactions in the ER.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

Transport between im/mobile fractions shapes the speed and profile of cargo distribution in neurons

Neuronal function requires continuous distribution of ion channels and other proteins throughout large cell morphologies. Protein distribution is complicated by immobilization of freely diffusing subunits such as on lipid rafts or in postsynaptic densities. Here, we infer rates of immobilization for the voltage-gated potassium channel Kv4.2. Fluorescence recovery after photobleaching quantifies protein diffusion kinetics, typically reported as a recovery rate and mobile fraction. We show that, implicit in the fluorescence recovery, are rates of particle transfer between mobile and immobile fractions (im/mobilization). We performed photobleaching of fluorescein-tagged ion channel Kv4.2-sGFP2 in over 450 dendrites of rat hippocampal cells. Using mass-action models, we infer rates of Kv4.2-sGFP2 im/mobilization. Using a realistic neuron morphology, we show how these rates shape the speed and profile of subunit distribution. The experimental protocol and model inference introduced here is widely applicable to other cargo and experimental systems.

Spatiotemporal analysis of axonal autophagosome-lysosome dynamics reveals limited fusion events and slow maturation

Macroautophagy is a homeostatic process required to clear cellular waste. Neuronal autophagosomes form constitutively in the distal tip of the axon and are actively transported toward the soma, with cargo degradation initiated en route. Cargo turnover requires autophagosomes to fuse with lysosomes to acquire degradative enzymes; however, directly imaging these fusion events in the axon is impractical. Here we use a quantitative model, parameterized and validated using data from primary hippocampal neurons, to explore the autophagosome maturation process. We demonstrate that retrograde autophagosome motility is independent of fusion and that most autophagosomes fuse with only a few lysosomes during axonal transport. Our results indicate that breakdown of the inner autophagosomal membrane is much slower in neurons than in nonneuronal cell types, highlighting the importance of this late maturation step. Together, rigorous quantitative measurements and mathematical modeling elucidate the dynamics of autophagosome-lysosome interaction and autophagosomal maturation in the axon.

Modeling transport of extended interacting objects with drop-off phenomenon

We study a deterministic framework for important cellular transport phenomena involving a large number of interacting molecules called the excluded flow of extended interacting objects with drop-off effect (EFEIOD). This model incorporates many realistic features of biological transport process including the length of biological "particles" and the fact that they can detach along the biological 'tracks'. The flow between the consecutive sites is unidirectional and is described by a "soft" simple exclusion principle and by repelling or attracting forces between neighboring particles. We show that the model admits a unique steady-state. Furthermore, if the parameters are periodic with common period T, then the steady-state profile converge to a unique periodic solution of period T. Simulations of the EFEIOD demonstrate several non-trivial effects of the interactions on the system steady-state profile. For example, detachment rates may help in increasing the steady-state flow by alleviating traffic jams that can exist due to several reasons like bottleneck rate or interactive forces between the particles. We also analyze the special case of our model, when there are no forces exerted by neighboring particles, and called it as the ribosome flow model of extended objects with drop-off effect (RFMEOD), and study the sensitivity of its steady-state to variations in the parameters.

The needs of a synapse—How local organelles serve synaptic proteostasis

Synaptic function crucially relies on the constant supply and removal of neuronal membranes. The morphological complexity of neurons poses a significant challenge for neuronal protein transport since the machineries for protein synthesis and degradation are mainly localized in the cell soma. In response to this unique challenge, local micro‐secretory systems have evolved that are adapted to the requirements of neuronal membrane protein proteostasis. However, our knowledge of how neuronal proteins are synthesized, trafficked to membranes, and eventually replaced and degraded remains scarce. Here, we review recent insights into membrane trafficking at synaptic sites and into the contribution of local organelles and micro‐secretory pathways to synaptic function. We describe the role of endoplasmic reticulum specializations in neurons, Golgi‐related organelles, and protein complexes like retromer in the synthesis and trafficking of synaptic transmembrane proteins. We discuss the contribution of autophagy and of proteasome‐mediated and endo‐lysosomal degradation to presynaptic proteostasis and synaptic function, as well as nondegradative roles of autophagosomes and lysosomes in signaling and synapse remodeling. We conclude that the complexity of neuronal cyto‐architecture necessitates long‐distance protein transport that combines degradation with signaling functions.

Morphology and Transport in Eukaryotic Cells

Transport of intracellular components relies on a variety of active and passive mechanisms, ranging from the diffusive spreading of small molecules over short distances to motor-driven motion across long distances. The cell-scale behavior of these mechanisms is fundamentally dependent on the morphology of the underlying cellular structures. Diffusion-limited reaction times can be qualitatively altered by the presence of occluding barriers or by confinement in complex architectures, such as those of reticulated organelles. Motor-driven transport is modulated by the architecture of cytoskeletal filaments that serve as transport highways. In this review, we discuss the impact of geometry on intracellular transport processes that fulfill a broad range of functional objectives, including delivery, distribution, and sorting of cellular components. By unraveling the interplay between morphology and transport efficiency, we aim to elucidate key structure-function relationships that govern the architecture of transport systems at the cellular scale. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Coordination of Local Translation, Membranous Organelle Trafficking, and Synaptic Plasticity in Neurons

Neurons are highly complex polarized cells, displaying an extraordinary degree of spatial compartmentalization. At presynaptic and postsynaptic sites, far from the cell body, local protein synthesis is utilized to continually modify the synaptic proteome, enabling rapid changes in protein production to support synaptic function. Synapses undergo diverse forms of plasticity, resulting in long-term, persistent changes in synapse strength, which are paramount for learning, memory, and cognition. It is now well-established that local translation of numerous synaptic proteins is essential for many forms of synaptic plasticity, and much work has gone into deciphering the strategies that neurons use to regulate activity-dependent protein synthesis. Recent studies have pointed to a coordination of the local mRNA translation required for synaptic plasticity and the trafficking of membranous organelles in neurons. This includes the co-trafficking of RNAs to their site of action using endosome/lysosome “transports,” the regulation of activity-dependent translation at synapses, and the role of mitochondria in fueling synaptic translation. Here, we review our current understanding of these mechanisms that impact local translation during synaptic plasticity, providing an overview of these novel and nuanced regulatory processes involving membranous organelles in neurons.

zapERtrap: A light-regulated ER release system reveals unexpected neuronal trafficking pathways

Here we introduce zapalog-mediated endoplasmic reticulum trap (zapERtrap), which allows one to use light to precisely trigger forward trafficking of diverse integral membrane proteins from internal secretory organelles to the cell surface with single cell and subcellular spatial resolution. To demonstrate its utility, we use zapERtrap in neurons to dissect where synaptic proteins emerge at the cell surface when processed through central (cell body) or remote (dendrites) secretory pathways. We reveal rapid and direct long-range trafficking of centrally processed proteins deep into the dendritic arbor to synaptic sites. Select proteins were also trafficked to the plasma membrane of the axon initial segment, revealing a novel surface trafficking hotspot. Proteins locally processed through dendritic secretory networks were widely dispersed before surface insertion, challenging assumptions for precise trafficking at remote sites. These experiments provide new insights into compartmentalized secretory trafficking and showcase the tunability and spatiotemporal control of zapERtrap, which will have broad applications for regulating cell signaling and function.

Optimizing mitochondrial maintenance in extended neuronal projections

Neurons rely on localized mitochondria to fulfill spatially heterogeneous metabolic demands. Mitochondrial aging occurs on timescales shorter than the neuronal lifespan, necessitating transport of fresh material from the soma. Maintaining an optimal distribution of healthy mitochondria requires an interplay between a stationary pool localized to sites of high metabolic demand and a motile pool capable of delivering new material. Interchange between these pools can occur via transient fusion / fission events or by halting and restarting entire mitochondria. Our quantitative model of neuronal mitostasis identifies key parameters that govern steady-state mitochondrial health at discrete locations. Very infrequent exchange between stationary and motile pools optimizes this system. Exchange via transient fusion allows for robust maintenance, which can be further improved by selective recycling through mitophagy. These results provide a framework for quantifying how perturbations in organelle transport and interactions affect mitochondrial homeostasis in neurons, a key aspect underlying many neurodegenerative disorders.

On the role of vesicle transport in neurite growth: Modeling and experiments

The processes that determine the establishment of the complex morphology of neurons during development are still poorly understood. Here, we focus on the question how a difference in the length of neurites affects vesicle transport. We performed live imaging experiments and present a lattice-based model to gain a deeper theoretical understanding of intracellular transport in neurons. After a motivation and appropriate scaling of the model we present numerical simulations showing that initial differences in neurite length result in phenomena of biological relevance, i.e. a positive feedback that enhances transport into the longer neurite and oscillation of vesicles concentrations that can be interpreted as cycles of extension and retraction observed in experiments. Thus, our model is a first step towards a better understanding of the interplay between the transport of vesicles and the spatial organization of cells.

Paradoxical relationships between active transport and global protein distributions in neurons

Neural function depends on continual synthesis and targeted trafficking of intracellular components, including ion channel proteins. Many kinds of ion channels are trafficked over long distances to specific cellular compartments. This raises the question of whether cargo is directed with high specificity during transit or whether cargo is distributed widely and sequestered at specific sites. We addressed this question by experimentally measuring transport and expression densities of Kv4.2, a voltage-gated transient potassium channel that exhibits a specific dendritic expression that increases with distance from the soma and little or no functional expression in axons. In over 500 h of quantitative live imaging, we found substantially higher densities of actively transported Kv4.2 subunits in axons as opposed to dendrites. This paradoxical relationship between functional expression and traffic density supports a model—commonly known as the sushi belt model—in which trafficking specificity is relatively low and active sequestration occurs in compartments where cargo is expressed. In further support of this model, we find that kinetics of active transport differs qualitatively between axons and dendrites, with axons exhibiting strong superdiffusivity, whereas dendritic transport resembles a weakly directed random walk, promoting mixing and opportunity for sequestration. Finally, we use our data to constrain a compartmental reaction-diffusion model that can recapitulate the known Kv4.2 density profile. Together, our results show how nontrivial expression patterns can be maintained over long distances with a relatively simple trafficking mechanism and how the hallmarks of a global trafficking mechanism can be revealed in the kinetics and density of cargo.

The Making of Long-Lasting Memories: A Fruit Fly Perspective

Understanding the nature of the molecular mechanisms underlying memory formation, consolidation, and forgetting are some of the fascinating questions in modern neuroscience. The encoding, stabilization and elimination of memories, rely on the structural reorganization of synapses. These changes will enable the facilitation or depression of neural activity in response to the acquisition of new information. In other words, these changes affect the weight of specific nodes within a neural network. We know that these plastic reorganizations require de novo protein synthesis in the context of Long-term memory (LTM). This process depends on neural activity triggered by the learned experience. The use of model organisms like Drosophila melanogaster has been proven essential for advancing our knowledge in the field of neuroscience. Flies offer an optimal combination of a more straightforward nervous system, composed of a limited number of cells, and while still displaying complex behaviors. Studies in Drosophila neuroscience, which expanded over several decades, have been critical for understanding the cellular and molecular mechanisms leading to the synaptic and behavioral plasticity occurring in the context of learning and memory. This is possible thanks to sophisticated technical approaches that enable precise control of gene expression in the fruit fly as well as neural manipulation, like chemogenetics, thermogenetics, or optogenetics. The search for the identity of genes expressed as a result of memory acquisition has been an active interest since the origins of behavioral genetics. From screenings of more or less specific candidates to broader studies based on transcriptome analysis, our understanding of the genetic control behind LTM has expanded exponentially in the past years. Here we review recent literature regarding how the formation of memories induces a rapid, extensive and, in many cases, transient wave of transcriptional activity. After a consolidation period, transcriptome changes seem more stable and likely represent the synthesis of new proteins. The complexity of the circuitry involved in memory formation and consolidation is such that there are localized changes in neural activity, both regarding temporal dynamics and the nature of neurons and subcellular locations affected, hence inducing specific temporal and localized changes in protein expression. Different types of neurons are recruited at different times into memory traces. In LTM, the synthesis of new proteins is required in specific subsets of cells. This de novo translation can take place in the somatic cytoplasm and/or locally in distinct zones of compartmentalized synaptic activity, depending on the nature of the proteins and the plasticity-inducing processes that occur. We will also review recent advances in understanding how localized changes are confined to the relevant synapse. These recent studies have led to exciting discoveries regarding proteins that were not previously involved in learning and memory processes. This invaluable information will lead to future functional studies on the roles that hundreds of new molecular actors play in modulating neural activity.

Synaptic activity and strength are reflected by changes in the post-synaptic secretory pathway

Neurons are highly asymmetric cells that span long distances and need to react promptly to local demands. Consequently, neuronal secretory pathway elements are distributed throughout neurites, specifically in post-synaptic compartments, to enable local protein synthesis and delivery. Whether and how changes in local synaptic activity correlate to post-synaptic secretory elements is still unclear. To assess this, we used STED nanoscopy and automated quantitative image analysis of post-synaptic markers of the endoplasmic reticulum, ER-Golgi intermediate compartment, trans-Golgi network, and spine apparatus. We found that the distribution of these proteins was dependent on pre-synaptic activity, measured as the amount of recycling vesicles. Moreover, their abundance correlated to both pre- and post-synaptic markers of synaptic strength. Overall, the results suggest that in small, low-activity synapses the secretory pathway components are tightly clustered in the synaptic area, presumably to enable rapid local responses, while bigger synapses utilise secretory machinery components from larger, more diffuse areas.

Statistical Laws of Protein Motion in Neuronal Dendritic Trees

Across their dendritic trees, neurons distribute thousands of protein species that are necessary for maintaining synaptic function and plasticity and that need to be produced continuously and trafficked to their final destination. As each dendritic branchpoint splits the protein flow, increasing branchpoints decreases the total protein number downstream. Consequently, a neuron needs to produce more proteins to maintain a minimal protein number at distal synapses. Combining in vitro experiments and a theoretical framework, we show that proteins that diffuse within the cell plasma membrane are, on average, 35% more effective at reaching downstream locations than proteins that diffuse in the cytoplasm. This advantage emerges from a bias for forward motion at branchpoints when proteins diffuse within the plasma membrane. Using 3D electron microscopy (EM) data, we show that pyramidal branching statistics and the diffusion lengths of common proteins fall into a region that minimizes the overall protein need.

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Surface proteins are more efficient at reaching distal sites than soluble proteins

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Daughter radius optimization reduces the number of proteins needed to populate dendrites

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Ratios of daughter radii at branchpoints are cell type specific

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Highly diffusive proteins incur a smaller extra cost for non-optimized radii

Activity-dependent compensation of cell size is vulnerable to targeted deletion of ion channels

In many species, excitable cells preserve their physiological properties despite significant variation in physical size across time and in a population. For example, neurons in crustacean central pattern generators generate similar firing patterns despite several-fold increases in size between juveniles and adults. This presents a biophysical problem because the electrical properties of cells are highly sensitive to membrane area and channel density. It is not known whether specific mechanisms exist to sense membrane area and adjust channel expression to keep a consistent channel density, or whether regulation mechanisms that sense activity alone are capable of compensating cell size. We show that destabilising effects of growth can be specifically compensated by feedback mechanism that senses average calcium influx and jointly regulate multiple conductances. However, we further show that this class of growth-compensating regulation schemes is necessarily sensitive to perturbations that alter the expression of subsets of ion channel types. Targeted perturbations of specific ion channels can trigger a pathological response of the regulation mechanism and a failure of homeostasis. Our findings suggest that physiological regulation mechanisms that confer robustness to growth may be specifically vulnerable to deletions or mutations that affect subsets of ion channels.

Simplicity, Flexibility, and Interpretability in a Model of Dendritic Protein Distributions

In this issue of Neuron, Fonkeu et al. (2019) present a mathematical model of mRNA and protein synthesis, degradation, diffusion, and trafficking in neuronal dendrites. The model can predict the spatial distribution and temporal dynamics of proteins along dendrites. The authors use the model to account for in situ imaging data of CaMKII⍺ mRNA and protein in hippocampal neurons.

How mRNA Localization and Protein Synthesis Sites Influence Dendritic Protein Distribution and Dynamics

Proteins drive the function of neuronal synapses. The synapses are distributed throughout the dendritic arbor, often hundreds of micrometers away from the soma. It is still unclear how somatic and dendritic sources of proteins shape protein distribution and respectively contribute to local protein changes during synaptic plasticity. Here, we present a unique computational framework describing for a given protein species the dendritic distribution of the mRNA and the corresponding protein in a dendrite. Using CaMKIIα as a test case, our model reveals the key role active transport plays in the maintenance of dendritic mRNA and protein levels and predicts the short and long timescales of protein dynamics. Our model reveals the fundamental role of mRNA localization and dendritic mRNA translation in synaptic maintenance and plasticity in distal compartments. We developed a web application for neuroscientists to explore the dynamics of the mRNA or protein of interest.

Live cell imaging reveals 3'-UTR dependent mRNA sorting to synapses

mRNA transport restricts translation to specific subcellular locations, which is the basis for many cellular functions. However, the precise process of mRNA sorting to synapses in neurons remains elusive. Here we use Rgs4 mRNA to investigate 3′-UTR-dependent transport by MS2 live-cell imaging. The majority of observed RNA granules display 3′-UTR independent bidirectional transport in dendrites. Importantly, the Rgs4 3′-UTR causes an anterograde transport bias, which requires the Staufen2 protein. Moreover, the 3′-UTR mediates dynamic, sustained mRNA recruitment to synapses. Visualization at high temporal resolution enables us to show mRNA patrolling dendrites, allowing transient interaction with multiple synapses, in agreement with the sushi-belt model. Modulation of neuronal activity by either chemical silencing or local glutamate uncaging regulates both the 3′-UTR-dependent transport bias and synaptic recruitment. This dynamic and reversible mRNA recruitment to active synapses would allow translation and synaptic remodeling in a spatially and temporally adaptive manner.

Asymmetric subcellular mRNA distribution is important for local translation of neuronal mRNAs. Here the authors employed MS2 live-cell imaging and showed that the reporter mRNA containing the 3’ UTR of Rgs4 shows an anterograde transport bias, dependent on neuronal activity and the protein Staufen2, and mediates sustained mRNA recruitment to synapses.

Architecture and Dynamics of the Neuronal Secretory Network

Regulated synthesis and movement of proteins between cellular organelles are central to diverse forms of biological adaptation and plasticity. In neurons, the repertoire of channel, receptor, and adhesion proteins displayed on the cell surface directly impacts cellular development, morphology, excitability, and synapse function. The immensity of the neuronal surface membrane and its division into distinct functional domains present a challenging landscape over which proteins must navigate to reach their appropriate functional domains. This problem becomes more complex considering that neuronal protein synthesis is continuously refined in space and time by neural activity. Here we review our current understanding of how integral membrane and secreted proteins important for neuronal function travel from their sites of synthesis to their functional destinations. We discuss how unique adaptations to the function and distribution of neuronal secretory organelles may facilitate local protein trafficking at remote sites in neuronal dendrites to support diverse forms of synaptic plasticity.

Competition for synaptic building blocks shapes synaptic plasticity

Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.

New approaches for solving old problems in neuronal protein trafficking

Fundamental cellular properties are determined by the repertoire and abundance of proteins displayed on the cell surface. As such, the trafficking mechanisms for establishing and maintaining the surface proteome must be tightly regulated for cells to respond appropriately to extracellular cues, yet plastic enough to adapt to ever-changing environments. Not only are the identity and abundance of surface proteins critical, but in many cases, their regulated spatial positioning within surface nanodomains can greatly impact their function. In the context of neuronal cell biology, surface levels and positioning of ion channels and neurotransmitter receptors play essential roles in establishing important properties, including cellular excitability and synaptic strength. Here we review our current understanding of the trafficking pathways that control the abundance and localization of proteins important for synaptic function and plasticity, as well as recent technological advances that are allowing the field to investigate protein trafficking with increasing spatiotemporal precision.

Neuronal messenger ribonucleoprotein transport follows an aging Lévy walk

Localization of messenger ribonucleoproteins (mRNPs) plays an essential role in the regulation of gene expression for long-term memory formation and neuronal development. Knowledge concerning the nature of neuronal mRNP transport is thus crucial for understanding how mRNPs are delivered to their target synapses. Here, we report experimental and theoretical evidence that the active transport dynamics of neuronal mRNPs, which is distinct from the previously reported motor-driven transport, follows an aging Lévy walk. Such nonergodic, transient superdiffusion occurs because of two competing dynamic phases: the motor-involved ballistic run and static localization of mRNPs. Our proposed Lévy walk model reproduces the experimentally extracted key dynamic characteristics of mRNPs with quantitative accuracy. Moreover, the aging status of mRNP particles in an experiment is inferred from the model. This study provides a predictive theoretical model for neuronal mRNP transport and offers insight into the active target search mechanism of mRNP particles in vivo.

Golgi-independent secretory trafficking through recycling endosomes in neuronal dendrites and spines

Neurons face the challenge of regulating the abundance, distribution and repertoire of integral membrane proteins within their immense, architecturally complex dendritic arbors. While the endoplasmic reticulum (ER) supports dendritic translation, most dendrites lack the Golgi apparatus (GA), an essential organelle for conventional secretory trafficking. Thus, whether secretory cargo is locally trafficked in dendrites through a non-canonical pathway remains a fundamental question. Here we define the dendritic trafficking itinerary for key synaptic molecules in rat cortical neurons. Following ER exit, the AMPA-type glutamate receptor GluA1 and neuroligin 1 undergo spatially restricted entry into the dendritic secretory pathway and accumulate in recycling endosomes (REs) located in dendrites and spines before reaching the plasma membrane. Surprisingly, GluA1 surface delivery occurred even when GA function was disrupted. Thus, in addition to their canonical role in protein recycling, REs also mediate forward secretory trafficking in neuronal dendrites and spines through a specialized GA-independent trafficking network.

All cells must produce, sort and deliver molecular building blocks to the right places at the right time and in appropriate amounts. This is particularly important for neurons, which are the largest and most structurally complex cells in the body. A typical neuron consists of a cell body covered in branches called dendrites, plus a single cable-like structure known as an axon. Dendrites receive inputs from other neurons and relay the information to the cell body in the form of electrical signals. The cell body processes these electrical signals and the resulting signals then travel along the axon to terminals at the far-end. The axon terminals in turn pass the signals on to the dendrites of other neurons via junctions called synapses.

For synapses to work correctly, the membranes surrounding the dendrites need to contain receptor proteins that can detect incoming signals. These proteins must be continually replenished, raising the question of how newly made receptor molecules are shuttled to the appropriate locations within the dendrites.

A series of compartments called the Golgi complex play an important role in processing newly-made proteins in many different types of cells. As proteins pass through the Golgi, enzymes within the tunnel walls modify the proteins by adding or removing molecular groups. Therefore, it has been suggested that the route that the synapse receptor proteins take through the neuron to reach the dendrites always includes a visit to the Golgi. However, the Golgi complex in neurons is mostly confined to the cell body, raising the question of whether proteins that are locally produced within dendrites can make the journey to nearby synapses without visiting the Golgi complex.

Bowen et al. used a microscope to follow the movements of synapse receptor proteins through neurons grown in a dish. The experiments show that proteins destined for the dendrites make a number of stops after leaving the cell body. However, some synaptic proteins reach the dendrites without passing through the Golgi at all, suggesting neurons are much less dependent on the Golgi to process newly-made proteins than other types of cells.

Genetic mutations that prevent proteins from finding their way to their required destinations, or that disrupt the work of enzymes inside trafficking stations like the Golgi, cause numerous human diseases. Understanding how proteins travel to specific destinations inside healthy cells should also help reveal what happens when this process fails.