MicroRNAs 99b-5p/100-5p regulated by endoplasmic reticulum stress are involved in Abeta-induced pathologies

Alzheimer’s disease (AD) is the most common cause of dementia. Amyloid beta (Abeta) deposition and intracellular tangles are the pathological hallmarks of AD. MicroRNAs (miRNAs) are small non-coding RNAs which have been found to play very important roles and have the potential to serve as diagnostic markers during neuronal pathogenesis. In this study, we aimed to determine the roles of miR-99b-5p and miR-100-5p in Abeta-induced neuronal pathologies. We detected the expression levels of miR-99b-5p and miR-100-5p in the brains of APPswe/PS1ΔE9 double transgenic mice (APP/PS1 mice) at different age stages and found both miRNAs were decreased at early stages while increased at late stages of APP/PS1 mice when compared with the age-matched wild type (WT) mice. Similar phenomenon was also observed in Abeta-treated cultured cells. We also confirmed that mTOR (mammalian target of rapamycin) is one of the targets of miR-99b-5p/100-5p, which is consistent with previous studies in cancer. MiR-99b-5p/100-5p have been found to promote cell apoptosis with the Abeta treatment. This effect may be induced via the mTOR pathway. In our study, we find both miR-99b-5p and miR-100-5p affect neuron survival by targeting mTOR. We also speculate that dynamic change of miR-99b-5p/100-5p levels during Abeta-associated pathologies might be attributed to Abeta-induced endoplasmic reticulum stress (ER stress), suggesting the potential role of the ER stress –miRNAs – mTOR axis in Abeta-related AD pathogenesis

A systematic simulation of the effect of salicylic acid on sphingolipid metabolism

The phytohormone salicylic acid (SA) affects plant development and defense responses. Recent studies revealed that SA also participates in the regulation of sphingolipid metabolism, but the details of this regulation remain to be explored. Here, we use in silico Flux Balance Analysis (FBA) with published microarray data to construct a whole-cell simulation model, including 23 pathways, 259 reactions, and 172 metabolites, to predict the alterations in flux of major sphingolipid species after treatment with exogenous SA. This model predicts significant changes in fluxes of certain sphingolipid species after SA treatment, changes that likely trigger downstream physiological and phenotypic effects. To validate the simulation, we used 15N-labeled metabolic turnover analysis to measure sphingolipid contents and turnover rate in Arabidopsis thaliana seedlings treated with SA or the SA analog benzothiadiazole (BTH). The results show that both SA and BTH affect sphingolipid metabolism, altering the concentrations of certain species and also changing the optimal flux distribution and turnover rate of sphingolipids. Our strategy allows us to estimate sphingolipid fluxes on a short time scale and gives us a systemic view of the effect of SA on sphingolipid homeostasis

Genetic variations in the serotonergic system contribute to amygdala volume in humans

The amygdala plays a critical role in emotion processing and psychiatric disorders associated with emotion dysfunction. Accumulating evidence suggests that amygdala structure is modulated by serotonin-related genes. However, there is a gap between the small contributions of single loci (less than 1%) and the reported 63-65% heritability of amygdala structure. To understand the "missing heritability," we systematically explored the contribution of serotonin genes on amygdala structure at the gene set level. The present study of 417 healthy Chinese volunteers examined 129 representative polymorphisms in genes from multiple biological mechanisms in the regulation of serotonin neurotransmission. A system-level approach using multiple regression analyses identified that nine SNPs collectively accounted for approximately 8% of the variance in amygdala volume. Permutation analyses showed that the probability of obtaining these findings by chance was low (p = 0.043, permuted for 1000 times). Findings showed that serotonin genes contribute moderately to individual differences in amygdala volume in a healthy Chinese sample. These results indicate that the system-level approach can help us to understand the genetic basis of a complex trait such as amygdala structure