Cancer cells, relative to normal cells, demonstrate increased sensitivity to glucose deprivation-induced cytotoxicity. To determine if oxidative stress mediated by O2•− and hydroperoxides contributed to the differential susceptibility of human epithelial cancer cells to glucose deprivation, oxidation of dihydroethidine (DHE; for O2•−) and 5-(and-6)-carboxy-2', 7'-dichlorodihydrofluorescein diacetate (CDCFH2; for hydroperoxides) were measured in human colon and breast cancer cells (HT29, HCT116, SW480, MB231) and compared to normal human cells (FHC, 33Co, HMEC). Cancer cells showed significant increases in DHE (2–20 fold) and CDCFH2 (1.8–10 fold) oxidation, relative to normal cells that were more pronounced in the presence of the mitochondrial electron transport chain blocker, antimycin A. Furthermore, HCT116 and MB231 cells were more susceptible to glucose deprivation-induced cytotoxicity and oxidative stress, relative to 33Co and HMEC. HT-29 cells were also more susceptible to 2-deoxyglucose-(2DG)-induced cytotoxicity, relative to FHC. Over expression of manganese superoxide dismutase and mitochondrially targeted catalase significantly protected HCT116 and MB231 cells from glucose deprivation-induced cytotoxicity and oxidative stress, as well as protecting HT-29 cells from 2DG-induced cytotoxicity. These results show cancer cells (relative to normal cells) demonstrate increased steady-state levels of reactive oxygen species (ROS, i.e. O2•− and H2O2) that contribute to differential susceptibility to glucose deprivation-induced cytotoxicity and oxidative stress. These studies support the hypotheses that cancer cells increase glucose metabolism to compensate for excess metabolic production of ROS as well as that inhibition of glucose and hydroperoxide metabolism may provide a biochemical target for selectively enhancing cytotoxicity and oxidative stress in human cancer cells.

Ras (Rat sarcoma) protein is a central regulator of cell growth and proliferation. Mutations in the RAS gene are known to occur in human cancers and have been shown to contribute to carcinogenesis. In this study, we show that the multifunctional-autoprocessing repeats-in-toxin (MARTX) toxin-effector domain DUF5Vv from Vibrio vulnificus to be a site-specific endopeptidase that cleaves within the Switch 1 region of Ras and Rap1. DUF5Vv processing of Ras, which occurs both biochemically and in mammalian cell culture, inactivates ERK1/2, thereby inhibiting cell proliferation. The ability to cleave Ras and Rap1 is shared by DUF5Vv homologues found in other bacteria. In addition, DUF5Vv can cleave all Ras isoforms and KRas with mutations commonly implicated in malignancies. Therefore, we speculate that this new family of Ras/Rap1-specific endopeptidases (RRSPs) has potential to inactivate both wild-type and mutant Ras proteins expressed in malignancies.

Pyruvate dehydrogenase E1 alpha (PDHE1α or PDHA1) is the first component enzyme of the pyruvate dehydrogenase (PDH) complex (PDC) that transforms pyruvate, via pyruvate decarboxylation, into acetyl-CoA that is subsequently used by both the citric acid cycle and oxidative phosphorylation to generate ATP. As such, PDH links glycolysis and oxidative phosphorylation in normal as well as cancer cells. Herein we report that SIRT3 interacts with PDHA1 and directs its enzymatic activity via changes in protein acetylation. SIRT3 deacetylates PDHA1 lysine 321 (K321) and a PDHA1 mutant, mimicking a deacetylated lysine (PDHA1K321R) increases in PDH activity, as compared to the K321 acetylation mimic (PDHA1K321Q) or wild-type PDHA1. Finally, PDHA1K321Q exhibited a more transformed in vitro cellular phenotype as compared to PDHA1K321R. These results suggest that the acetylation of PDHA1 provides another layer of enzymatic regulation, in addition to phosphorylation, involving a reversible acetyl-lysine suggesting that the acetylome, as well as the kinome, links glycolysis to respiration.

Background Unmanned aerial vehicle (UAV)-based remote sensing provides a flexible, low-cost, and efficient approach to monitor crop growth status at fine spatial and temporal resolutions, and has a high potential to accelerate breeding process and improve precision field management. Method In this study, we discussed the use of lightweight UAV with dual image-frame snapshot cameras to estimate aboveground biomass (AGB) and panicle biomass (PB) of rice at different growth stages with different nitrogen (N) treatments. The spatial–temporal variations in the typical vegetation indices (VIs) and AGB were first investigated, and the accuracy of crop surface model (CSM) extracted from the Red Green Blue (RGB) images at two different stages were also evaluated. Random forest (RF) model for AGB estimation as well as the PB was then developed. Furthermore, variable importance and sensitivity analysis of UAV variables were performed to study the potential of improving model robustness and prediction accuracies. Results It was found that the canopy height extracted from the CSM (Hcsm) exhibited a high correlation with the ground-measured canopy height, while it was unsuitable to be independently used for biomass assessment of rice during the entire growth stages. We also observed that several VIs were highly correlated with AGB, and the modified normalized difference spectral index extracted from the multispectral image achieved the highest correlation. RF model with fusing RGB and multispectral image data substantially improved the prediction results of AGB and PB with the prediction of root mean square error (RMSEP) reduced by 8.33–16.00%. The best prediction results for AGB and PB were achieved with the coefficient of determination (r 2 ), the RMSEP and relative RMSE (RRMSE) of 0.90, 0.21 kg/m 2 and 14.05%, and 0.68, 0.10 kg/m 2 and 12.11%, respectively. In addition, the result confirmed that the sensitivity analysis could simplify the prediction model without reducing the prediction accuracy. Conclusion These findings demonstrate the feasibility of applying lightweight UAV with dual image-frame snapshot cameras for rice biomass estimation, and its potential for high throughput analysis of plant growth-related traits in precision agriculture as well as the advanced breeding program. Electronic supplementary material The online version of this article (10.1186/s13007-019-0418-8) contains supplementary material, which is available to authorized users.