AxonQuant: A Microfluidic Chamber Culture-Coupled Algorithm That Allows High-Throughput Quantification of Axonal Damage

Abstract

Published methods for imaging and quantitatively analyzing morphological changes in neuronal axons have serious limitations because of their small sample sizes, and their time-consuming and nonobjective nature. Here we present an improved microfluidic chamber design suitable for fast and high-throughput imaging of neuronal axons. We developed the AxonQuant algorithm, which is suitable for automatic processing of axonal imaging data. This microfluidic chamber-coupled algorithm allows calculation of an ‘axonal continuity index' that quantitatively measures axonal health status in a manner independent of neuronal or axonal density. This method allows quantitative analysis of axonal morphology in an automatic and nonbiased manner. Our method will facilitate large-scale high-throughput screening for genes or therapeutic compounds for neurodegenerative diseases involving axonal damage. When combined with imaging technologies utilizing different gene markers, this method will provide new insights into the mechanistic basis for axon degeneration. Our microfluidic chamber culture-coupled AxonQuant algorithm will be widely useful for studying axonal biology and neurodegenerative disorders. © 2014 S. Karger AG, Basel

A new method for quantifying mitochondrial axonal transport

“…1A and 1B; also see Li et al, 2014). Several improvements were made based on published designs (Cui et al, 2007; Zhang et al, 2010), including reducing the overall size of the microfluidic device and decreasing the space between the microgrooves.…”

“…This may not best reflect physiological conditions in which the majority of axons exist as axonal bundles rather than isolated individual axons. To image axonal mitochondrial transport in axonal bundles, we used a micro-fluidic chamber system for culturing neurons that we previously established (Li et al, 2014) and optimized real-time fluorescent confocal microscopy on a Leica SP8 system. Our newly established method made it possible to image a large number of mitochondria simultaneously at a time resolution up to 1 Hz.…”

“…We followed established protocols to fabricate microfluidic chambers (Cui et al, 2007; Li et al, 2014). Briefly, masks were designed with AutoCAD (Autodesk).…”

Quantitative and semi-quantitative measurements of axonal degeneration in tissue and primary neuron cultures

“…Some of the analysis methods are manual while others have varying levels of automation. For example, the AxonQuant image analysis method is designed for high-throughput analysis of microfluidic devices and uses a custom algorithm to deliver accurate measures of degenerating axons; however, the complicated design of this method makes it less approachable than simpler image analysis methodologies [20]. The length of axons can be measured in 2D monolayer cell cultures using the petrimetrics stereological probe [21].…”

Deep learning to decipher the progression and morphology of axonal degeneration

“…The reason may be two-fold: 1) Available software relies on image binarization 14,15 , which can lead to information loss and low sensitivity as thin axons may not be recognized. 2) The analysis requires subjective and time-consuming manual annotations, e.g., thresholding and defining the region of interest [16][17][18] . So far, immunostained images were used to investigate morphological changes in AxD as the analysis of phase-contrast images has been limited by the lower target-to-background signal.…”