The Action of D-Dopachrome Tautomerase as an Adipokine in Adipocyte Lipid Metabolism

Adipose tissue is a critical exchange center for complex energy transactions involving triacylglycerol storage and release. It also has an active endocrine role, releasing various adipose-derived cytokines (adipokines) that participate in complex pathways to maintain metabolic and vascular health. Here, we found D-dopachrome tautomerase (DDT) as an adipokine secreted from human adipocytes by a proteomic approach. DDT mRNA levels in human adipocytes were negatively correlated with obesity-related clinical parameters such as BMI, and visceral and subcutaneous fat areas. Experiments using SGBS cells, a human preadipocyte cell line, revealed that DDT mRNA levels were increased in an adipocyte differentiationdependent manner and DDT was secreted from adipocytes. In DDT knockdown adipocytes differentiated from SGBS cells that were infected with the adenovirus expressing shRNA against the DDT gene, mRNA levels of genes involved in both lipolysis and lipogenesis were slightly but significantly increased. Furthermore, we investigated AMP-activated protein kinase (AMPK) signaling, which phosphorylates and inactivates enzymes involved in lipid metabolism, including hormonesensitive lipase (HSL) and acetyl-CoA carboxylase (ACC), in DDT knockdown adipocytes. The AMPK phosphorylation of HSL Ser-565 and ACC Ser-79 was inhibited in DDT knockdown cells and recovered in the cells treated with recombinant DDT (rDDT), suggesting that down-regulated DDT in adipocytes brings about a state of active lipid metabolism. Furthermore, administration of rDDT in db/db mice improved glucose intolerance and decreased serum free fatty acids levels. In the adipose tissue from rDDT-treated db/db mice, not only increased levels of HSL phosphorylated by AMPK, but also decreased levels of HSL phosphorylated by protein kinase A (PKA), which phosphorylates HSL to promote its activity, were observed. These results suggested that DDT acts on adipocytes to regulate lipid metabolism through AMPK and/or PKA pathway(s) and improves glucose intolerance caused by obesity

Plant viruses and viroids in Japan

An increasing number of plant viruses and viroids have been reported from all over the world due largely to metavirogenomics approaches with technological innovation. Herein, the official changes of virus taxonomy, including the establishment of megataxonomy and amendments of the codes of virus classification and nomenclature, recently made by the International Committee on Taxonomy of Viruses were summarized. The continued efforts of the plant virology community of Japan to index all plant viruses and viroids occurring in Japan, which represent 407 viruses, including 303 virus species and 104 unclassified viruses, and 25 viroids, including 20 species and 5 unclassified viroids, as of October 2021, were also introduced. These viruses and viroids are collectively classified into 81 genera within 26 families of 3 kingdoms (Shotokuvirae, Orthornavirae, Pararnavirae) across 2 realms (Monodnaviria and Riboviria). This review also overviewed how Japan’s plant virus/viroid studies have contributed to advance virus/viroid taxonomy

Stimulus-Dependent Adjustment of Reward Prediction Error in the Midbrain

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus–reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus