Substrate docking and molecular dynamic simulation for prediction of fungal enzymes from Trichoderma species-assisted extraction of nanocellulose from oil palm leaves

Abstract

Fungi of the Trichoderma species are valued industrial enzymes in support of the ‘zero-waste’ technology to convert agro-industrial biomass into valuable products, i.e. nanocellulose (NC). In this study, an in silico approach using substrate docking and molecular dynamic (MD) simulation was used to predict the order of which the multilayers of cellulosic polymers, i.e. lignin, hemicellulose and cellulose in oil palm leaves (OPL) are degraded by fungal enzymes, endocellulase and exocellulase. The study aimed to establish the catalytic tendencies of the enzymes to optimally degrade the cellulosic components of OPL for high yield production of NC. Energy minimized endocellulase and exocellulase models revealed satisfactory scores of PROCHECK (90.0% and 91.2%), Verify3D (97.23% and 98.85%) and ERRAT (95.24% and 91.00%) assessments. Active site prediction by blind docking, COACH meta-server and multiple sequence alignment indicated the catalytic triads for endocellulase and exocellulase were Ser116–His205–Glu249 and Ser382–Arg124–Asp385, respectively. Binding energy of endocellulase docked with hemicellulose (?6.0 ? kcal mol^?1) was the most favourable followed by lignin (?5.6 ? kcal mol^?1) and cellulose (?4.4 ? kcal mol^?1). Exocellulase, contrarily, bonded favorably with lignin (?8.7 ? kcal mol^?1), closely followed by cellulose (?8.5 ? kcal mol^?1) and hemicellulose (?8.4 ? kcal mol^?1). MDs simulations showed that interactions of complexes, endocellulase–hemicellulose and the exocellulase–cellulose being the most stable. Thus, the findings of the study successfully identified the specific actions of sugar-acting enzymes for NC production.

Communicated by Ramaswamy H. Sarma     

Cardioprotective role of extracellular vesicles: A highlight on exosome beneficial effects in cardiovascular diseases

Extracellular vesicles (EVs) are nano-sized vesicles, released from many cell types including cardiac cells, have recently emerged as intercellular communication tools in cell dynamics. EVs are an important mediator of signaling within cells that influencing the functional behavior of the target cells. In heart complex, cardiac cells can easily use EVs to transport bioactive molecules such as proteins, lipids, and RNAs to the regulation of neighboring cell function. Cross-talk between intracardiac cells plays pivotal roles in the heart homeostasis and in adaptive responses of the heart to stress. EVs were released by cardiomyocytes under baseline conditions, but stress condition such as hypoxia intensifies secretome capacity. EVs secreted by cardiac progenitor cells and cardiosphere-derived cells could be pinpointed as important mediators of cardioprotection and cardiogenesis. Furthermore, EVs from many different types of stem cells could potentially exert a therapeutic effect on the damaged heart. Recent evidence shows that cardiac-derived EVs are rich in microRNAs, suggesting a key role in the controlling of cellular processes. EVs harboring exosomes may be clinically useful in cell-free therapy approaches and potentially act as prognosis and diagnosis biomarkers of cardiovascular diseases.     

Testing the Equality of Dependent Variances

The likelihood ratio test for testing equality of vgE;2 correlated variables is developed. In general, evaluation of the test statistic involves the iterative optimization of a likelihood function with 1 + v(v – 1)/2 parameters. The explicit form of the test statistic is derived in the bivariate case, and an iterative algorithm for determining the maximum likelihood estimates is suggested. A limited Monte Carlo study determines the behavior of the proposed procedure under the null hypothesis and variety of parameter values.     

Study of the Effect of Surfactants on Extraction and Determination of Polyphenolic Compounds and Antioxidant Capacity of Fruits Extracts

Micelle/water mixed solutions of different surface active agents were studied for their effectiveness in the extraction of polyphenolic compounds from various varieties of apples from west Azerbaijan province in Iran. The total content of polyphenolic compound in fruit extracts were determined using ferrous tartrate and Folin–Ciocalteu assays methods and chromatographic methods and compared with theme. High performance liquid chromatography is one of the most common and important methods in biochemical compound identification. The effect of pH, ionic strength, surfactant type, surfactant concentration, extraction time and common organic solvent in the apple polyphenolics extractions was studied using HPLC-DAD. Mixtures of surfactants, water and methanol at various ratios were examined and micellar-water solutions of Brij surfactant showed the highest polyphenol extraction efficiency. Optimum conditions for the extraction of polyphenolic compounds from apple occurred at 7 mM Brij35, pH 3. Effect of ionic strength on extraction was determined and 2% (W/V) potassium Chloride was determined to be the optimum salt concentration. The procedure worked well with an ultrasound bath. Total antioxidant capacity also was determined in this study. The method can be safely scaled up for pharmaceutical applications.     

Targeting age‐specific changes in CD4+ T cell metabolism ameliorates alloimmune responses and prolongs graft survival

Age impacts alloimmunity. Effects of aging on T‐cell metabolism and the potential to interfere with immunosuppressants have not been explored yet. Here, we dissected metabolic pathways of CD4⁺ and CD8⁺ T cells in aging and offer novel immunosuppressive targets. Upon activation, CD4⁺ T cells from old mice failed to exhibit adequate metabolic reprogramming resulting into compromised metabolic pathways, including oxidative phosphorylation (OXPHOS) and glycolysis. Comparable results were also observed in elderly human patients. Although glutaminolysis remained the dominant and age‐independent source of mitochondria for activated CD4⁺ T cells, old but not young CD4⁺ T cells relied heavily on glutaminolysis. Treating young and old murine and human CD4⁺ T cells with 6‐diazo‐5‐oxo‐l‐norleucine (DON), a glutaminolysis inhibitor resulted in significantly reduced IFN‐γ production and compromised proliferative capacities specifically of old CD4⁺ T cells. Of translational relevance, old and young mice that had been transplanted with fully mismatched skin grafts and treated with DON demonstrated dampened Th1‐ and Th17‐driven alloimmune responses. Moreover, DON diminished cytokine production and proliferation of old CD4⁺ T cells in vivo leading to a significantly prolonged allograft survival specifically in old recipients. Graft prolongation in young animals, in contrast, was only achieved when DON was applied in combination with an inhibition of glycolysis (2‐deoxy‐d‐glucose, 2‐DG) and OXPHOS (metformin), two alternative metabolic pathways. Notably, metabolic treatment had not been linked to toxicities. Remarkably, immunosuppressive capacities of DON were specific to CD4⁺ T cells as adoptively transferred young CD4⁺ T cells prevented immunosuppressive capacities of DON on allograft survival in old recipients. Depletion of CD8⁺ T cells did not alter transplant outcomes in either young or old recipients. Taken together, our data introduce an age‐specific metabolic reprogramming of CD4⁺ T cells. Targeting those pathways offers novel and age‐specific approaches for immunosuppression.     

An Evidence-Based Combining Classifier for Brain Signal Analysis

Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems.     

Specific Localization of β-Arrestin2 in Myenteric Plexus of Mouse Gastrointestinal Tract

β-arrestin2 is a key molecule involved in signaling and internalization of activated G protein-coupled receptors including µ-opioid receptors (MOR). Previously we have shown that decreased expression of β-arrestin2 upon chronic morphine is associated with the development of opioid tolerance in the gastrointestinal tract. However, the localization of β-arrestin2 within the gastrointestinal wall is not known. In this study we found that β-arrestin2 is localized in the soma of a select group of neurons in the myenteric ganglia but not in smooth muscle. The density of β-arestin2 was significantly higher in the ileum than the colon. We identified four variants of β-arrestin2 in the ileum, with ARRB-005 and ARRB-013 being the most abundant. Further, the current study utilized multiple-labeling immunofluorescence to characterize the chemical coding of neurons expressing β-arrestin2 in the murine myenteric plexus and the co-localization of MOR₁ and β-arrestin2. β-arrestin2 co-localized with choline acetyltransferase and calretinin. In contrast, β-arrestin2 neither co-localized with substance P, nitric oxide synthase nor calbindin. Genetic deletion of β-arrestin2 did not affect cholinergic neuron activation by nicotine in the isolated ileum (-log M EC₅₀: wild type = 5.8 vs. β-arrestin2 knockout = 5.9). Our findings suggest specificity in the localization of β-arrestin2 in the myenteric plexus within MOR₁-expressing neurons and provide a relation for direct intracellular crosstalk between MOR₁ receptor activation and β-arrestin2 signaling in the myenteric neurons. β-arrestin2 deletion does not directly alter basal enteric cholinergic neuronal function.