A coupled model of fast axonal transport of organelles and slow axonal transport of tau protein

The interplay of active and passive mechanisms in slow axonal transport

A combination of intermittent active movement of transient aggregates and a paused state that intervenes between periods of active transport has been proposed to underlie the slow, directed transport of soluble proteins in axons. A component of passive diffusion in the axoplasm may also contribute to slow axonal transport, although quantitative estimates of the relative contributions of diffusive and active movement in the slow transport of a soluble protein, and in particular how they might vary across developmental stages, are lacking. Here, we propose and study a model for slow axonal transport, addressing data from bleach recovery measurements on a small, soluble, protein, choline acetyltransferase, in thin axons of the lateral chordotonal (lch5) sensory neurons of Drosophila. Choline acetyltransferase is mainly present in soluble form in the axon and catalyzes the acetylation of choline at the synapse. It does not form particulate structures in axons and moves at rates characteristic of slow component b (≈ 1-10 mm/day or 0.01-0.1 μm/s). Using our model, which incorporates active transport with paused and/or diffusive states, we predict bleach recovery, transport rates, and cargo trajectories obtained through kymographs, comparing these with experimental observations at different developmental stages. We show that changes in the diffusive fraction of cargo during these developmental stages dominate bleach recovery and that a combination of active motion with a paused state alone cannot reproduce the data. We compared predictions of the model with results from photoactivation experiments. The importance of the diffusive state in reproducing the bleach recovery signal in the slow axonal transport of small soluble proteins is our central result.

Hyperphosphorylated Human Tau Accumulates at the Synapse, Localizing on Synaptic Mitochondrial Outer Membranes and Disrupting Respiration in a Mouse Model of Tauopathy

Neurogenerative disorders, such as Alzheimer’s disease (AD), represent a growing public health challenge in aging societies. Tauopathies, a subset of neurodegenerative disorders that includes AD, are characterized by accumulation of fibrillar and hyperphosphorylated forms of microtubule-associated protein tau with coincident mitochondrial abnormalities and neuronal dysfunction. Although, in vitro, tau impairs axonal transport altering mitochondrial distribution, clear in vivo mechanisms associating tau and mitochondrial dysfunction remain obscure. Herein, we investigated the effects of human tau on brain mitochondria in vivo using transgenic htau mice at ages preceding and coinciding with onset of tauopathy. Subcellular proteomics combined with bioenergetic assessment revealed pathologic forms of tau preferentially associate with synaptic over non-synaptic mitochondria coinciding with changes in bioenergetics, reminiscent of an aged synaptic mitochondrial phenotype in wild-type mice. While mitochondrial content was unaltered, mitochondrial maximal respiration was impaired in synaptosomes from htau mice. Further, mitochondria-associated tau was determined to be outer membrane-associated using the trypsin protection assay and carbonate extraction. These findings reveal non-mutant human tau accumulation at the synapse has deleterious effects on mitochondria, which likely contributes to synaptic dysfunction observed in the context of tauopathy.

Simulating the effect of formation of amyloid plaques on aggregation of tau protein

In this paper, we develop a mathematical model that enables the investigation of the production and intracellular transport of amyloid precursor protein (APP) and tau protein in a neuron. We also investigate the aggregation of APP fragments into amyloid-β (Aβ) as well as tau aggregation into tau oligomers and neurofibrillary tangles. Using the developed model, we investigate how Aβ aggregation can influence tau transport and aggregation in both the soma and the axon. We couple the Aβ and tau agglomeration processes by assuming that the value of the kinetic constant that describes the autocatalytic growth (self-replication) reaction step of tau aggregation is proportional to the Aβ concentration. The model predicts that APP and tau are distributed differently in the axon. While APP has a uniform distribution along the axon, tau's concentration first decreases and then increases towards the synapse. Aβ is uniformly produced along the axon while misfolded tau protein is mostly produced in the proximal axon. The number of Aβ and tau polymers originating from the axon is much smaller than the number of Aβ and tau polymers originating from the soma. The rate of production of misfolded tau polymers depends on how strongly their production is facilitated by Aβ.

How the formation of amyloid plaques and neurofibrillary tangles may be related: a mathematical modelling study

We develop a mathematical model that enables us to investigate possible mechanisms by which two primary markers of Alzheimer's disease (AD), extracellular amyloid plaques and intracellular tangles, may be related. Our model investigates the possibility that the decay of anterograde axonal transport of amyloid precursor protein (APP), caused by toxic tau aggregates, leads to decreased APP transport towards the synapse and APP accumulation in the soma. The developed model thus couples three processes: (i) slow axonal transport of tau, (ii) tau misfolding and agglomeration, which we simulated by using the Finke-Watzky model and (iii) fast axonal transport of APP. Because the timescale for tau agglomeration is much larger than that for tau transport, we suggest using the quasi-steady-state approximation for formulating and solving the governing equations for these three processes. Our results suggest that misfolded tau most likely accumulates in the beginning of the axon. The analysis of APP transport suggests that APP will also likely accumulate in the beginning of the axon, causing an increased APP concentration in this region, which could be interpreted as a 'traffic jam'. The APP flux towards the synapse is significantly reduced by tau misfolding, but not due to the APP traffic jam, which can be viewed as a symptom, but rather due to the reduced affinity of kinesin-1 motors to APP-transporting vesicles.

Protein phosphatase 2A and tau: an orchestrated 'Pas de Deux'

The neuronal microtubule-associated protein tau serves a critical role in regulating axonal microtubule dynamics to support neuronal and synaptic functions. Furthermore, it contributes to glutamatergic regulation and synaptic plasticity. Emerging evidence also suggests that tau serves as a signaling scaffold. Tau function and subcellular localization are tightly regulated, in part, by the orchestrated interplay between phosphorylation and dephosphorylation events. Significantly, protein phosphatase type 2A (PP2A), encompassing the regulatory PPP2R2A (or Bα) subunit, is a major brain heterotrimeric enzyme and the primary tau Ser/Thr phosphatase in vivo. Herein, we closely examine how the intimate and compartmentalized interactions between PP2A and tau regulate tau phosphorylation and function, and play an essential role in neuronal homeostasis. We also review evidence supporting a strong link between deregulation of tau-PP2A functional interactions and the molecular underpinnings of various neurodegenerative diseases collectively called tauopathies. Lastly, we discuss the opportunities and associated challenges in more specifically targeting PP2A-tau interactions for drug development for tauopathies.

What mechanisms of tau protein transport could be responsible for the inverted tau concentration gradient in degenerating axons?

In tauopathies, such as Alzheimer's disease (AD), microtubule (MT)-associated protein tau detaches from MTs and aggregates, eventually forming insoluble neurofibrillary tangles. In a healthy axon, the tau concentration increases toward the axon terminal, but in a degenerating axon, the tau concentration gradient is inverted and the highest tau concentration is in the soma. In this article, we developed a mathematical model of tau transport in axons. We calibrated and tested the model by using published distributions of tau concentration and tau average velocity in a healthy axon. According to published research, the inverted tau concentration gradient may be one of the reasons leading to AD. We therefore used the model to investigate what modifications in tau transport can lead to the inverted tau concentration gradient. We investigated whether tau detachment from MTs due to tau hyperphosphorylation can cause the inverted tau concentration gradient. We found that the assumption that most tau molecules are detached from MTs does not consistently predict the inverted tau concentration gradient; the predicted tau distribution becomes more uniform if the axon length is increased. We then hypothesized that in degenerating axons some tau remains bound to MTs and participates in the component 'a' of slow axonal transport but that the rate of tau reversals from anterograde to retrograde motion increases. We demonstrated that this hypothesis results in a tau distribution where the tau concentration has its maximum value at the axon hillock and its minimum value at the axon terminal, in agreement with what is observed in AD. Our results thus suggest that defects in active transport of tau may be a contributing factor to the onset of neural degeneration.

Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate 'experimental' data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

Peloruside A: a lead non-taxoid-site microtubule-stabilizing agent with potential activity against cancer, neurodegeneration, and autoimmune disease

Covering: 2000 up to 2016Peloruside A, a macrocyclic secondary metabolite from a New Zealand marine sponge, Mycale hentscheli, has shown potent antiproliferative activity in cultured cancer cells as well as inhibitory effects on tumor growth in mouse models. The compound also has promising effects against cell models of neurodegenerative and autoimmune diseases. In mechanistic studies, peloruside A shares with paclitaxel (Taxol®) the ability to stabilize microtubules by binding to β-tubulin. Peloruside A, however, occupies a unique external site on β-tubulin that does not overlap the classical taxoid site that is located on the inside of the microtubule. As such, peloruside A has been of central importance in defining a new microtubule-stabilizer binding site localized on the exterior surface of the microtubule that has led to increased interest in the design of an upscaled total synthesis of the natural product and its analogues. Here, we review advances in the biochemical and biological validation of peloruside A as an attractive therapeutic candidate for the treatment of cancer, neurodegeneration, and autoimmune disease.

Can numerical modeling help understand the fate of tau protein in the axon terminal?

In this paper, we used mathematical modeling to investigate the fate of tau protein in the axon terminal. We developed a comprehensive model of tau transport that accounts for transport of cytosolic tau by diffusion, diffusion transport of microtubule (MT)-bound tau along the MT lattice, active motor-driven transport of MT-bound tau via slow axonal transport mechanism, and degradation of tau in the axon due to tau's finite half-life. We investigated the effect of different assumptions concerning the fate of tau in the terminal on steady-state transport of tau in the axon. In particular, we studied two possible scenarios: (i) tau is destroyed in the terminal and (ii) there is no tau destruction in the terminal, and to avoid tau accumulation we postulated zero flux of tau at the terminal. We found that the tau concentration and percentage of MT-bound tau are not very sensitive to the assumption concerning the fate of tau in the terminal, but the tau's flux and average velocity of tau transport are very sensitive to this assumption. This suggests that measuring the velocity of tau transport and comparing it with the results of mathematical modeling for different assumptions concerning tau's fate in the terminal can provide information concerning what happens to tau in the terminal.