RESUMEN
Neuroinflammation, a hallmark of chronic neurodegenerative disorders, is characterized by sustained glial activation and the generation of an inflammatory loop, through the release of cytokines and other neurotoxic mediators that cause oxidative stress and limit functional repair of brain parenchyma. Dietary antioxidants may protect against neurodegenerative diseases by counteracting chronic neuroinflammation and reducing oxidative stress. Here, we describe the effects of a number of natural antioxidants (polyphenols, carotenoids, and thiolic molecules) in rescuing astrocytic function and neuronal viability following glial activation by reducing astrocyte proliferation and restoring astrocytic and neuronal survival and basal levels of reactive oxygen species (ROS). All antioxidant molecules are also effective under conditions of oxidative stress and glutamate toxicity, two maladaptive components of neuroinflammatory processes. Moreover, it is remarkable that their antioxidant and anti-inflammatory activity occurs through differential modulation of NF-κB binding activity in neurons and astrocytes. In fact, we show that inflammatory stimuli promote a significant induction of NF-κB binding activity in astrocytes and its concomitant reduction in neurons. These changes are prevented in astrocytes and neurons pretreated with the antioxidant molecules, suggesting that NF-κB plays a key role in the modulation of survival and anti-inflammatory responses. Finally, we newly demonstrate that effective antigliosis and neuroprotective activity is achieved with a defined cocktail of four natural antioxidants at very low concentrations, suggesting a promising strategy to reduce inflammatory and oxidative damage in neurodegenerative diseases with limited side effects.
Asunto(s)
Antioxidantes/metabolismo , Astrocitos/metabolismo , FN-kappa B/genética , Enfermedades Neurodegenerativas/genética , Neuroprotección/genética , Estrés Oxidativo/genética , HumanosRESUMEN
Neuronal differentiation involves extensive modification of biochemical and morphological properties to meet novel functional requirements. Reorganization of the mitochondrial network to match the higher energy demand plays a pivotal role in this process. Mechanisms of neuronal differentiation in response to nerve growth factor (NGF) have been largely characterized in terms of signaling, however, little is known about its impact on mitochondrial remodeling and metabolic function. In this work, we show that NGF-induced differentiation requires the activation of autophagy mediated by Atg9b and Ambra1, as it is disrupted by their genetic knockdown and by autophagy blockers. NGF differentiation involves the induction of P-AMPK and P-CaMK, and is prevented by their pharmacological inhibition. These molecular events correlate with modifications of energy and redox homeostasis, as determined by ATP and NADPH changes, higher oxygen consumption (OCR) and ROS production. Our data indicate that autophagy aims to clear out exhausted mitochondria, as determined by enhanced localization of p62 and Lysotracker-red to mitochondria. In addition, we newly demonstrate that NGF differentiation is accompanied by increased mitochondrial remodeling involving higher levels of fission (P-Drp1) and fusion proteins (Opa1 and Mfn2), as well as induction of Sirt3 and the transcription factors mtTFA and PPARγ, which regulate mitochondria biogenesis and metabolism to sustain increased mitochondrial mass, potential, and bioenergetics. Overall, our data indicate a new NGF-dependent mechanism involving mitophagy and extensive mitochondrial remodeling, which plays a key role in both neurogenesis and nerve regeneration.
Asunto(s)
Diferenciación Celular , Mitocondrias/metabolismo , Factor de Crecimiento Nervioso/metabolismo , Neuronas/citología , Neuronas/metabolismo , Proteínas Adaptadoras Transductoras de Señales/genética , Proteínas Adaptadoras Transductoras de Señales/metabolismo , Adenosina Trifosfato/metabolismo , Animales , Autofagia , Metabolismo Energético , Homeostasis , Ratones , Mitocondrias/genética , Células PC12 , RatasRESUMEN
BACKGROUND: Recent advances in large datasets analysis offer new insights to modern biology allowing system-level investigation of pathologies. Here we describe a novel computational method that exploits the ever-growing amount of "omics" data to shed light on Alzheimer's and Parkinson's diseases. Neurological disorders exhibit a huge number of molecular alterations due to a complex interplay between genetic and environmental factors. Classical reductionist approaches are focused on a few elements, providing a narrow overview of the etiopathogenic complexity of multifactorial diseases. On the other hand, high-throughput technologies allow the evaluation of many components of biological systems and their behaviors. Analysis of Parkinson's Disease (PD) and Alzheimer's Disease (AD) from a network perspective can highlight proteins or pathways common but differently represented that can be discriminating between the two pathological conditions, thus highlight similarities and differences. RESULTS: In this work we propose a strategy that exploits network community structure identified with a state-of-the-art network community discovery algorithm called InfoMap, which takes advantage of information theory principles. We used two similarity measurements to quantify functional and topological similarities between the two pathologies. We built a Similarity Matrix to highlight similar communities and we analyzed statistically significant GO terms found in clustered areas of the matrix and in network communities. Our strategy allowed us to identify common known and unknown processes including DNA repair, RNA metabolism and glucose metabolism not detected with simple GO enrichment analysis. In particular, we were able to capture the connection between mitochondrial dysfunction and metabolism (glucose and glutamate/glutamine). CONCLUSIONS: This approach allows the identification of communities present in both pathologies which highlight common biological processes. Conversely, the identification of communities without any counterpart can be used to investigate processes that are characteristic of only one of the two pathologies. In general, the same strategy can be applied to compare any pair of biological networks.