Perineuronal nets
We characterise the biophysical properties of PNNs, and how this relates to PNN functions
Background
Perineuronal nets (PNNs) are extracellular matrix structures which develop around some neurons as they mature. By enwrapping neurons, PNNs act to maintain synaptic connections once formed but also impede the formation of new synaptic connections, thus limiting neuronal plasticity.
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PNNs are organised structures of cross-linked glycans and proteins with distinct morphologies and physical properties, enabling them to form a barrier to extending axons and damaging molecules. Hyaluronan is a long-chain glycosaminoglycan (GAG) and forms the backbone of PNNs. Chondroitin sulphate proteoglycans (CSPGs) connect to hyaluronan by link proteins, and further proteins (e.g., Tenascin-R) link multiple CSPGs together thus contributing to the condensed PNN structure.
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PNNs are implicated in a range of diseases such as schizophrenia and epilepsy. Understanding more about their structures may provide a therapeutic target to treat these disorders in the future. Due to their multifunctional roles of protecting neurons and regulating synaptic plasticity, PNNs cannot just be removed, so research is needed to understand how to manipulate these structures without causing detriment for disease treatment. We seek to understand the molecular and physical mechanisms that underpin PNN formation and functions.
Scroll below to see more about the formation of PNNs around neurons as they mature
Immature neuron
Tools used
Axons are able to make connections with this neuron since PNNs have not developed yet
As neurons mature, PNN structures develop, limiting the ability of extending axons to form synapses with the neuron. In less mature neurons, PNN structures are found to be more granular.
PNNs form robust reticular structures around mature neurons, so it is difficult for any extending axons to form synapses, potentially reducing synaptic plasticity.
Tools used within our research
Click on each icon to learn more about the technique, and how it is used in our research
To analyse how proteins bind
and cross-link PNN glycans
To make molecularly defined
PNN models
To characterise the topography and mechanics of neurons
To label and image PNN components and self-organisation
To analyse how proteins
cross-link PNN glycans