What is it about?
Our research uses mathematical modeling to understand how tau protein moves through the AIS, a specific region at the beginning of a neuron's axon. We developed a model simulating tau in seven different kinetic states to analyze how it interacts with microtubules and molecular motors. We discovered that when free tau binds to microtubules, it creates a concentration gradient that pulls more free tau from the main cell body (soma) into the AIS via diffusion. As tau moves further down the AIS, it switches from this diffusion-based movement to being actively carried anterogradely by molecular motors.
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Why is it important?
This is the first mathematical model to describe tau transport specifically within the AIS. It is crucial because the malfunction of tau transport and its loss of enrichment in the axon are early signs of Alzheimer's disease and other tauopathies. Previously, it was suggested that the AIS acted merely as a barrier to counteract diffusion, but our model shows it functions as an active pump where diffusion and motor-driven transport work together. Understanding this normal cellular pumping mechanism helps us figure out what breaks down during the onset of neurodegeneration.
Perspectives
Working on this collaborative project between North Carolina State University and the University of Pennsylvania was an exciting opportunity to apply engineering principles to a complex biological problem. It was deeply rewarding to mathematically demonstrate how a region previously thought of as just a diffusion barrier actually operates as a highly coordinated cellular pump. I hope this work demonstrates the power of computational modeling in unraveling the physical mechanisms behind neurodegenerative diseases. Ultimately, combining quantitative mathematical models with biological data is essential for advancing our understanding of Alzheimer's disease.
Andrey V Kuznetsov
North Carolina State University
Read the Original
This page is a summary of: Modeling tau transport in the axon initial segment, Mathematical Biosciences, November 2020, Elsevier,
DOI: 10.1016/j.mbs.2020.108468.
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