Spatiotemporal expression patterns of chondroitin sulfate proteoglycan mRNAs in the developing rat brain

Proteoglycans and Glycosaminoglycans in Stem Cell Homeostasis and Bone Tissue Regeneration

Stem cells maintain a subtle balance between self-renewal and differentiation under the regulatory network supported by both intracellular and extracellular components. Proteoglycans are large glycoproteins present abundantly on the cell surface and in the extracellular matrix where they play pivotal roles in facilitating signaling transduction and maintaining stem cell homeostasis. In this review, we outline distinct proteoglycans profiles and their functions in the regulation of stem cell homeostasis, as well as recent progress and prospects of utilizing proteoglycans/glycosaminoglycans as a novel glycomics carrier or bio-active molecules in bone regeneration.

Multiple Particle Tracking Detects Changes in Brain Extracellular Matrix and Predicts Neurodevelopmental Age

Brain extracellular matrix (ECM) structure mediates many aspects of neural development and function. Probing structural changes in brain ECM could thus provide insights into mechanisms of neurodevelopment, the loss of neural function in response to injury, and the detrimental effects of pathological aging and neurological disease. We demonstrate the ability to probe changes in brain ECM microstructure using multiple particle tracking (MPT). We performed MPT of colloidally stable polystyrene nanoparticles in organotypic rat brain slices collected from rats aged 14-70 days old. Our analysis revealed an inverse relationship between nanoparticle diffusive ability in the brain extracellular space and age. Additionally, the distribution of effective ECM pore sizes in the cortex shifted to smaller pores throughout development. We used the raw data and features extracted from nanoparticle trajectories to train a boosted decision tree capable of predicting chronological age with high accuracy. Collectively, this work demonstrates the utility of combining MPT with machine learning for measuring changes in brain ECM structure and predicting associated complex features such as chronological age. This will enable further understanding of the roles brain ECM play in development and aging and the specific mechanisms through which injuries cause aberrant neuronal function. Additionally, this approach has the potential to develop machine learning models capable of detecting the presence of injury or indicating the extent of injury based on changes in the brain microenvironment microstructure.

The roles of perineuronal nets and the perinodal extracellular matrix in neuronal function

Perineuronal nets (PNNs) are extracellular matrix (ECM) chondroitin sulfate proteoglycan (CSPG)-containing structures that surround the soma and dendrites of various mammalian neuronal cell types. PNNs appear during development around the time that the critical periods for developmental plasticity end and are important for both their onset and closure. A similar structure - the perinodal ECM - surrounds the axonal nodes of Ranvier and appears as myelination is completed, acting as an ion-diffusion barrier that affects axonal conduction speed. Recent work has revealed the importance of PNNs in controlling plasticity in the CNS. Digestion, blocking or removal of PNNs influences functional recovery after a variety of CNS lesions. PNNs have further been shown to be involved in the regulation of memory and have been implicated in a number of psychiatric disorders.