Enterovirus 71 (EV71) infection is an endemic disease in Southeast Asia and China. We have previously shown that EV71 virus causes functional changes in mitochondria. It is speculative whether EV71 virus alters the host cell metabolism to its own benefit. Using a metabolomics approach, we demonstrate that EV71-infected Vero cells had significant changes in metabolism. Glutathione and its related metabolites, and several amino acids, such as glutamate and aspartate, changed significantly with the infectious dose of virus. Other pathways, including glycolysis and tricarboxylic acid cycle, were also altered. A change in glutamine/glutamate metabolism is critical to the viral infection. The presence of glutamine in culture medium was associated with an increase in viral replication. Dimethyl α-ketoglutarate treatment partially mimicked the effect of glutamine supplementation. In addition, the immunoblot analysis revealed that the expression of glutamate dehydrogenase (GDH) and trifunctional carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) increased during infection. Knockdown of expression of glutaminase (GLS), GDH and CAD drastically reduced the cytopathic effect (CPE) and viral replication. Furthermore, we found that CAD bound VP1 to promote the de novo pyrimidine synthesis. Our findings suggest that virus may induce metabolic reprogramming of host cells to promote its replication through interactions between viral and host cell proteins.

We have previously shown that GSH depletion alters global metabolism of cells. In the present study, we applied a metabolomic approach for studying the early changes in metabolism in hydrogen peroxide- (H2O2-) treated hepatoma cells which were destined to die. Levels of fructose 1,6-bisphosphate and an unusual metabolite, sedoheptulose 1,7-bisphosphate (S-1,7-BP), were elevated in hepatoma Hep G2 cells. Deficiency in G6PD activity significantly reduced S-1,7-BP formation, suggesting that S-1,7-BP is formed in the pentose phosphate pathway as a response to oxidative stress. Additionally, H2O2 treatment significantly increased the level of nicotinamide adenine dinucleotide phosphate (NADP+) and reduced the levels of ATP and NAD+. Severe depletion of ATP and NAD+ in H2O2-treated Hep G2 cells was associated with cell death. Inhibition of PARP-mediated NAD+ depletion partially protected cells from death. Comparison of metabolite profiles of G6PD-deficient cells and their normal counterparts revealed that changes in GSH and GSSG per se do not cause cell death. These findings suggest that the failure of hepatoma cells to maintain energy metabolism in the midst of oxidative stress may cause cell death.

Enterovirus (EV) 71 caused episodes of outbreaks in China and Southeast Asia during the last few decades. We have previously reported that EV71 induces reactive oxygen species (ROS). However, the underlying mechanism remains elusive. Co-immunoprecipitation-proteomic analysis revealed that enteroviral 2B protein interacted with mitochondrial voltage-dependent anion channel 3 (VDAC3). Knockdown (KD) of VDAC3 expression specifically inhibited enteroviral replication. Single-round viral replication was also inhibited in KD cells, suggesting that VDAC3 plays an essential role in replication. Consistent with this, VDAC3 gene KD significantly reduced the EV71-induced mitochondrial ROS generation. Exogenous 2B expression could induce the mitochondrial ROS generation that was significantly reduced in VDAC3-KD cells or in the Mito-TEMPO-treated cells. Moreover, VDAC3 appears to be necessary for regulation of antioxidant metabolism. VDAC3 gene KD led to the enhancement of such pathways as hypotaurine/taurine synthesis in the infected cells. Taken together, these findings suggest that 2B and VDAC3 interact to enhance mitochondrial ROS generation, which promotes viral replication.

The life cycle of leaves, from sprout to senescence, is the phenomenon of regular changes such as budding, branching, leaf spreading, flowering, fruiting, leaf fall, and dormancy due to seasonal climate changes. It is the effect of temperature and moisture in the life cycle on physiological changes, so the detection of newly grown leaves (NGL) is helpful for the estimation of tree growth and even climate change. This study focused on the detection of NGL based on deep learning convolutional neural network (CNN) models with sparse enhancement (SE). As the NGL areas found in forest images have similar sparse characteristics, we used a sparse image to enhance the signal of the NGL. The difference between the NGL and the background could be further improved. We then proposed hybrid CNN models that combined U-net and SegNet features to perform image segmentation. As the NGL in the image were relatively small and tiny targets, in terms of data characteristics, they also belonged to the problem of imbalanced data. Therefore, this paper further proposed 3-Layer SegNet, 3-Layer U-SegNet, 2-Layer U-SegNet, and 2-Layer Conv-U-SegNet architectures to reduce the pooling degree of traditional semantic segmentation models, and used a loss function to increase the weight of the NGL. According to the experimental results, our proposed algorithms were indeed helpful for the image segmentation of NGL and could achieve better kappa results by 0.743.