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Updated: Jan 2, 2026

Author Spotlight: Developing Tools to Tune the Activity of Tyrosine Phosphatases
Published on: September 6, 2024
The protein tyrosine phosphatase RPTPζ/phosphacan is critical for perineuronal net structure
Geoffrey J Eill1, Ashis Sinha1, Markus Morawski2
1Department of Neuroscience and Physiology, State University of New York Upstate Medical University, Syracuse, New York 13210.
Abstract:
Perineuronal nets (PNNs) are conspicuous neuron-specific substructures within the extracellular matrix of the central nervous system that have generated an explosion of interest over the last decade. These reticulated structures appear to surround synapses on the cell bodies of a subset of the neurons in the central nervous system and play key roles in both developmental and adult-brain plasticity. Despite the interest in these structures and compelling demonstrations of their importance in regulating plasticity, their precise functional mechanisms remain elusive. The limited mechanistic understanding of PNNs is primarily because of an incomplete knowledge of their molecular composition and structure and a failure to identify PNN-specific targets. Thus, it has been challenging to precisely manipulate PNNs to rigorously investigate their function. Here, using mouse models and neuronal cultures, we demonstrate a role of receptor protein tyrosine phosphatase zeta (RPTPζ) in PNN structure. We found that in the absence of RPTPζ, the reticular structure of PNNs is lost and phenocopies the PNN structural abnormalities observed in tenascin-R knockout brains. Furthermore, we biochemically analyzed the contribution of RPTPζ to PNN formation and structure, which enabled us to generate a more detailed model for PNNs. We provide evidence for two distinct kinds of interactions of PNN components with the neuronal surface, one dependent on RPTPζ and the other requiring the glycosaminoglycan hyaluronan. We propose that these findings offer important insight into PNN structure and lay important groundwork for future strategies to specifically disrupt PNNs to precisely dissect their function.
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