The microbiota is a complex ecosystem of microorganisms consisting of bacteria, viruses, protozoa, and fungi, living in different districts of the human body, such as the gastro-enteric tube, skin, mouth, respiratory system, and the vagina. Over 70% of the microbiota lives in the gastrointestinal tract in a mutually beneficial relationship with its host. The microbiota plays a major role in many metabolic functions, including modulation of glucose and lipid homeostasis, regulation of satiety, production of energy and vitamins. It exerts a role in the regulation of several biochemical and physiological mechanisms through the production of metabolites and substances. In addition, the microbiota has important anti-carcinogenetic and anti-inflammatory actions. There is growing evidence that any modification in the microbiota composition can lead to several diseases, including metabolic diseases, such as obesity and diabetes, and cardiovascular diseases. This is because alterations in the microbiota composition can cause insulin resistance, inflammation, vascular, and metabolic disorders. The causes of the microbiota alterations and the mechanisms by which microbiota modifications can act on the development of metabolic and cardiovascular diseases have been reported. Current and future preventive and therapeutic strategies to prevent these diseases by an adequate modulation of the microbiota have been also discussed.

Age-related macular degeneration (AMD) is the most common reason of visual impairment in the elderly in the Western countries. The degeneration of retinal pigment epithelial cells (RPE) causes secondarily adverse effects on neural retina leading to visual loss. The aging characteristics of the RPE involve lysosomal accumulation of lipofuscin and extracellular protein aggregates called “drusen”. Molecular mechanisms behind protein aggregations are weakly understood. There is intriguing evidence suggesting that protein SQSTM1/p62, together with autophagy, has a role in the pathology of different degenerative diseases. It appears that SQSTM1/p62 is a connecting link between autophagy and proteasome mediated proteolysis, and expressed strongly under the exposure to various oxidative stimuli and proteasomal inhibition. ELAVL1/HuR protein is a post-transcriptional factor, which acts mainly as a positive regulator of gene expression by binding to specific mRNAs whose corresponding proteins are fundamental for key cellular functions. We here show that, under proteasomal inhibitor MG-132, ELAVL1/HuR is up-regulated at both mRNA and protein levels, and that this protein binds and post-transcriptionally regulates SQSTM1/p62 mRNA in ARPE-19 cell line. Furthermore, we observed that proteasomal inhibition caused accumulation of SQSTM1/p62 bound irreversibly to perinuclear protein aggregates. The addition of the AMPK activator AICAR was pro-survival and promoted cleansing by autophagy of the former complex, but not of the ELAVL1/HuR accumulation, indeed suggesting that SQSTM1/p62 is decreased through autophagy-mediated degradation, while ELAVL1/HuR through the proteasomal pathway. Interestingly, when compared to human controls, AMD donor samples show strong SQSTM1/p62 rather than ELAVL1/HuR accumulation in the drusen rich macular area suggesting impaired autophagy in the pathology of AMD.

Neuronal ELAV-like proteins (HuB, HuC, and HuD) are highly conserved RNA-binding proteins able to selectively associate with the 3 UTR of a subset of target mRNAs and increase their cytoplasmic stability and rate of translation. We previously demonstrated the involvement of these proteins in learning, reporting that they undergo a sustained up-regulation in the hippocampus of mice trained in a spatial discrimination task. Here, we extend this finding, showing that a similar up-regulation occurs in the hippocampus of rats trained in another spatial learning paradigm, the Morris water maze. HuD, a strictly neuron-specific ELAV-like protein, is shown to increase after learning, with a preferential binding to the cytoskeletal fraction. HuD up-regulation is associated with an enhancement of GAP-43 mRNA and protein levels, with an apparently increased HuD colocalization with the GAP-43 mRNA and an increased association of neuronal ELAV-like proteins with the GAP-43 mRNA. These learning-dependent biochemical events appear to be spatiotemporally controlled, because they do not occur in another brain region involved in learning, the retrosplenial cortex, and at the level of protein expression they show extinction 1 month after training despite memory retention. By contrast, HuD mRNA levels still remain increased after 1 month in the CA1 region. This persistence may have implications for long-term memory recall.