New preprint: a mechanism for the slow axonal transport of actin

Another work in our fruitful collaboration with Subhojit Roy and his lab (now at UW Madison). In 2015 we could visualize new axonal actin structures by STORM (see our cover): stable clusters every 3-4 µm we called “hotspots” from which “trails” would rapidly assemble and disassemble along the axon. In this new preprint, trails were shown to have a slight anterograde bias (55%) and to polymerize from the surface of the hotspots, pushing the trails away. This suggested that biased dynamic trails assembly could underlie the slow anterograde transport of actin, whose mechanism is still unknown. Modelling done by Nilaj Chakrabarty and Peter Jung (Ohio University) indeed showed that the observed biased assembly and disassembly of trails would lead to a ~0.5 mm/day transport of actin, in line with earlier measurements.

Two collaborative papers out in the Journal of Neuroscience

In collaboration with Matt Rasband’s lab in Houston, we characterized the α-spectrin that is present along axons at the axon initial segment (AIS) and nodes of Ranvier. This work is out today as two back-to-back paper just pre-published on the Journal of Neuroscience website, here and here. Spectrins are tetramers of two α and two β subunits. It is known that the β-spectrin form at the AIS and nodes is the ßIV-spectrin since 2000, but the identity of the α subunit was unknown. In the axon, spectrins binds submembrane actin rings regularly spaced every 190 nm. As this is just below the resolution limit of conventional fluorescence microscopy (~200 nm), the resulting periodic scaffold is only visible using super-resolutive techniques such as STORM.

The first paper: “αII spectrin forms a periodic cytoskeleton at the axon initial segment and is required for nervous system function” focuses on the identification of αII-spectrin as the ßIV-spectrin partner at the AIS, and the consequences of αII-spectrin depletion in CNS-specific knockout mice. We used super-resolution microscopy to show that αII-spectrin is integrated in the AIS periodic actin/spectrin scaffold that supports the axonal plasma membrane. With the αII-spectrin antibody we used, the periodicity is seen as double bands every 190 nm by STORM. When using 2-color DNA-PAINT to image αII-spectrin together with ßIV-spectrin, the doublet of αII-spectrin labeling appears on both sides of the ßIV-spectrin bands, resolving the organization of the spectrin tetramers in situ. We also showed by STORM that the periodic actin/spectrin complex is disorganized in αII-spectrin-depleted neurons.

The second paper: “An αII spectrin based cytoskeleton protects large diameter Myelinated axons from degeneration” focuses on αII-spectrin in the PNS and nodes of Ranvier. In C. elegans mutants, the submembrane spectrin scaffold is necessary for the mechanical resistance of axons. Here, an αII-spectrin knockout mouse specific to peripheral sensory neurons was used to demonstrate this for in a vertebrate. Using STORM, we showed that loss of αII-spectrin causes a disorganization of the periodic scaffold at and around nodes. This disorganization ultimately results in the degeneration of large-diameter peripheral axons lacking  αII-spectrin.

Welcome Angélique to the team

After having worked in the lab for its M1 and M2 master internships, today we’re happy to welcome Angélique Jimenez in the team as an assistant engineer. Angélique will work on various project, including bridging live-cell imaging with super-resolution microscopy to study axonal actin.

New preprint: NanoJ-SQUIRREL

A new preprint is out today on bioRxiv. This collaboration with the Ricardo Henriques and Jason Mercer labs proposes a new metric to measure the quality of super-resolution images. Simply put, it compares the image to a reference diffraction-limited image, allowing to detect  artefacts and missing features in the super-resolved image. We used it to determine when to stop a STORM acquisition when visualizing axonal actin rings, and to optimize the dye concentration in a DNA-PAINT experiment. The method, called NanoJ-SQUIRREL (Super-resolution Quantitative Image Rating and Reporting of Error Locations), is available as an easy to use, open-source plugin for the ImageJ/Fiji plugin software. Try it!