Semaphorin 3A-Glycosaminoglycans Interaction as Therapeutic Target for Axonal Regeneration

Glycosaminoglycans: Mechanisms and therapeutic potential in neurological diseases: A mini-review

Glycosaminoglycans (GAGs) are vital polysaccharides that constitute key elements of the extracellular matrix (ECM), particularly within chondroitin sulfate proteoglycans (CSPGs). GAGs exhibit a dual role in neural tissue: they facilitate synaptic plasticity and cellular adhesion, essential for neural function, while posing as barriers to axonal regeneration following injury. Through interactions with diverse proteins, including enzymes, cytokines, and growth factors, GAGs critically influence neural development, repair, and homeostasis. Recent advancements have underscored the therapeutic potential of modulating GAG synthesis, degradation, and receptor interactions to address neuroinflammation, promote neural repair, and counteract inhibitory signals in the injured CNS. Furthermore, combining GAG-targeted therapies with complementary approaches, such as gene therapy or nanoparticle-based delivery systems, holds promise for achieving synergistic effects and enhancing treatment outcomes. This mini-review explores the multifaceted roles of GAGs in neural physiology and pathology, highlighting their emerging potential as therapeutic targets for neurological disorders.

Molecular mechanisms of proteoglycan-mediated semaphorin signaling in axon guidance

The precise assembly of a functional nervous system relies on axon guidance cues. Beyond engaging their cognate receptors and initiating signaling cascades that modulate cytoskeletal dynamics, guidance cues also bind components of the extracellular matrix, notably proteoglycans, yet the role and mechanisms of these interactions remain poorly understood. We found that Drosophila secreted semaphorins bind specifically to glycosaminoglycan (GAG) chains of proteoglycans, showing a preference based on the degree of sulfation. Structural analysis of Sema2b unveiled multiple GAG-binding sites positioned outside canonical plexin-binding site, with the highest affinity binding site located at the C-terminal tail, characterized by a lysine-rich helical arrangement that appears to be conserved across secreted semaphorins. In vivo studies revealed a crucial role of the Sema2b C-terminal tail in specifying the trajectory of olfactory receptor neurons. We propose that secreted semaphorins tether to the cell surface through interactions with GAG chains of proteoglycans, facilitating their presentation to cognate receptors on passing axons.

Morphogenetic theory of mental and cognitive disorders: the role of neurotrophic and guidance molecules

Mental illness and cognitive disorders represent a serious problem for the modern society. Many studies indicate that mental disorders are polygenic and that impaired brain development may lay the ground for their manifestation. Neural tissue development is a complex and multistage process that involves a large number of distant and contact molecules. In this review, we have considered the key steps of brain morphogenesis, and the major molecule families involved in these process. The review provides many indications of the important contribution of the brain development process and correct functioning of certain genes to human mental health. To our knowledge, this comprehensive review is one of the first in this field. We suppose that this review may be useful to novice researchers and clinicians wishing to navigate the field.

Epigallocatechin-3-gallate alleviates gestational stress-induced postpartum anxiety and depression-like behaviors in mice by downregulating semaphorin3A and promoting GSK3β phosphorylation in the hippocampus

Introduction

Postpartum depression (PPD) is a common neuropsychiatric disorder characterized by depression and comorbid anxiety during the postpartum period. PPD is difficult to treat because of its elusive mechanisms. Epigallocatechin-3-gallate (EGCG), a component of tea polyphenols, is reported to exert neuroprotective effects in emotional disorders by reducing inflammation and apoptosis. However, the effect of EGCG on PPD and the underlying mechanism are unknown.

Methods

We used a mouse model of PPD established by exposing pregnant mice to gestational stress. Open field, forced swimming and tail suspension tests were performed to investigate the anxiety and depression-like behaviors. Immunohistochemical staining was used to measure the c-fos positive cells. The transcriptional levels of hippocampal semaphorin3A(sema3A), (glycogen synthase kinase 3-beta)GSK3β and collapsin response mediator protein 2(CRMP2) were assessed by RT-PCR. Alterations in protein expression of Sema3A, GSK3β, p-GSK3β, CRMP2 and p-CRMP2 were quantified by western blotting. EGCG was administrated to analyze its effect on PPD mice.

Results

Gestational stress induced anxiety and depression-like behaviors during the postpartum period, increasing Sema3A expression while decreasing that of phosphorylated GSK3β as well as c-Fos in the hippocampus. These effects were reversed by systemic administration of EGCG.

Conclusions

Thus, EGCG may alleviate anxiety and depression-like behaviors in mice by downregulating Sema3A and increasing GSK3β phosphorylation in the hippocampus, and has potential application in the treatment of PPD.

Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships

Leveraging molecular networks to discover disease-relevant modules is a long-standing challenge. With the accumulation of interactomes, there is a pressing need for powerful computational approaches to handle the inevitable noise and context-specific nature of biological networks. Here, we introduce Graphene, a two-step self-supervised representation learning framework tailored to concisely integrate multiple molecular networks and adapted to gene functional analysis via downstream re-training. In practice, we first leverage GNN (graph neural network) pre-training techniques to obtain initial node embeddings followed by re-training Graphene using a graph attention architecture, achieving superior performance over competing methods for pathway gene recovery, disease gene reprioritization, and comorbidity prediction. Graphene successfully recapitulates tissue-specific gene expression across disease spectrum and demonstrates shared heritability of common mental disorders. Graphene can be updated with new interactomes or other omics features. Graphene holds promise to decipher gene function under network context and refine GWAS (genome-wide association study) hits and offers mechanistic insights via decoding diseases from genome to networks to phenotypes.