Resveratrol depletes mitochondrial DNA and inhibition of autophagy enhances resveratrol-induced caspase activation

We recently demonstrated that resveratrol induces caspase-dependent apoptosis in multiple cancer cell types. Whether apoptosis is also regulated by other cell death mechanisms such as autophagy is not clearly defined. Here we show that inhibition of autophagy enhanced resveratrol-induced caspase activation and apoptosis. Resveratrol inhibited colony formation and cell proliferation in multiple cancer cell types. Resveratrol treatment induced accumulation of LC3-II, which is a key marker for autophagy. Pretreatment with 3-methyladenine (3-MA), an autophagy inhibitor, increased resveratrol-mediated caspase activation and cell death in breast and colon cancer cells. Inhibition of autophagy by silencing key autophagy regulators such as ATG5 and Beclin-1 enhanced resveratrol-induced caspase activation. Mechanistic analysis revealed that Beclin-1 did not interact with proapoptotic proteins Bax and Bak; however, Beclin-1 was found to interact with p53 in the cytosol and mitochondria upon resveratrol treatment. Importantly, resveratrol depleted ATPase 8 gene, and thus, reduced mitochondrial DNA (mtDNA) content, suggesting that resveratrol induces damage to mtDNA causing accumulation of dysfunctional mitochondria triggering autophagy induction. Together, our findings indicate that induction of autophagy during resveratrol-induced apoptosis is an adaptive response.     

Nitrogen fixation ability explains leaf chemistry and arbuscular mycorrhizal responses to fertilization

Atmospheric nitrogen (N) and phosphorus (P) deposition rates are predicted to drastically increase in the coming decades. The ecosystem level consequences of these increases will depend on how plant tissue nutrient concentrations, stoichiometry and investment in nutrient uptake mechanisms such as arbuscular mycorrhizal fungi (AMF) change in response to increased nutrient availability, and how responses differ between plant functional types. Using a factorial nutrient addition experiment with seedlings of multiple N-fixing and non-N-fixing tree species, we examined whether leaf chemistry and AMF responses differ between these dominant woody plant functional groups of tropical savanna and dry forest ecosystems. We found that N-fixers have remarkably stable foliar chemistry that stays constant with external input of nutrients. Non-N-fixers responded to N and N + P addition by increasing both concentrations and total amounts of foliar N, but showed a corresponding decrease in P concentrations while total amounts of foliar P stayed constant, suggesting a ‘dilution’ of tissue P with increased N availability. Non-N-fixers also showed an increase in N:P ratios with N and N + P addition, probably driven by both an increase in N and a decrease in P concentrations. AMF colonization decreased with N + P addition in non-N-fixers and increased with N and N + P addition in N-fixers, suggesting differences in their nutrient acquisition roles in the two plant functional groups. Our results suggest that N-fixers and non-N-fixers can differ significantly in their responses to N and P deposition, with potential consequences for future nutrient and carbon cycling in savanna and dry forest ecosystems.     

Phosphorelays Provide Tunable Signal Processing Capabilities for the Cell

Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements; measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays.     

A molecular insight into papaya leaf curl—a severe viral disease

Papaya leaf curl disease (PaLCuD) caused by papaya leaf curl virus (PaLCuV) not only affects yield but also plant growth and fruit size and quality of papaya and is one of the most damaging and economically important disease. Management of PaLCuV is a challenging task due to diversity of viral strains, the alternate hosts, and the genomic complexities of the viruses. Several management strategies currently used by plant virologists to broadly control or eliminate the viruses have been discussed. In the absence of such strategies in the case of PaLCuV at present, the few available options to control the disease include methods like removal of affected plants from the field, insecticide treatments against the insect vector (Bemisia tabaci), and gene-specific control through transgenic constructs. This review presents the current understanding of papaya leaf curl disease, genomic components including satellite DNA associated with the virus, wide host and vector range, and management of the disease and suggests possible generic resistance strategies.     

Hypocholesterolemic Effect of Potent Peptide and Bioactive Fraction from Pigeon Pea By-Products in Wistar Rats

International Journal of Peptide Research and Therapeutics - Elevation high plasma cholesterol plays a significant role in promoting the incidence of atherosclerosis and coronary heart disease. In...     

Black Spot: a platform for automated and rapid estimation of leaf area from scanned images

Leaf area and its derivatives (e.g. specific leaf area) are widely used in ecological assessments, especially in the fields of plant–animal interactions, plant community assembly, ecosystem functioning and global change. Estimating leaf area is highly time-consuming, even when using specialized software to process scanned leaf images, because manual inputs are invariably required for scale detection and leaf surface digitisation. We introduce Black Spot Leaf Area Calculator (hereafter, Black Spot), a technique and stand-alone software package for rapid and automated leaf area assessment from images of leaves taken with standard flatbed scanners. Black Spot operates on comprehensive rule-sets for colour band ratios to carry out pixel-based classification which isolates leaf surfaces from the image background. Importantly, the software extracts information from associated image meta-data to detect image scale, thereby eliminating the need for time-consuming manual scale calibration. Black Spot’s output provides the user with estimates of leaf area as well as classified images for error checking. We tested this method and software combination on a set of 100 leaves of 51 different plant species collected from the field. Leaf area estimates generated using Black Spot and by manual processing of the images using an image editing software generated statistically identical results. Mean error rate in leaf area estimates from Black Spot relative to manual processing was ?0.4 % (SD = 0.76). The key advantage of Black Spot is the ability to rapidly batch process multi-species datasets with minimal user effort and at low cost, thus making it a valuable tool for field ecologists.