TCA cycle remodeling drives proinflammatory signaling in humans with pulmonary tuberculosis

The metabolic signaling pathways that drive pathologic tissue inflammation and damage in humans with pulmonary tuberculosis (TB) are not well understood. Using combined methods in plasma high-resolution metabolomics, lipidomics and cytokine profiling from a multicohort study of humans with pulmonary TB disease, we discovered that IL-1β-mediated inflammatory signaling was closely associated with TCA cycle remodeling, characterized by accumulation of the proinflammatory metabolite succinate and decreased concentrations of the anti-inflammatory metabolite itaconate. This inflammatory metabolic response was particularly active in persons with multidrug-resistant (MDR)-TB that received at least 2 months of ineffective treatment and was only reversed after 1 year of appropriate anti-TB chemotherapy. Both succinate and IL-1β were significantly associated with proinflammatory lipid signaling, including increases in the products of phospholipase A2, increased arachidonic acid formation, and metabolism of arachidonic acid to proinflammatory eicosanoids. Together, these results indicate that decreased itaconate and accumulation of succinate and other TCA cycle intermediates is associated with IL-1β-mediated proinflammatory eicosanoid signaling in pulmonary TB disease. These findings support host metabolic remodeling as a key driver of pathologic inflammation in human TB disease.     

Genetic Predisposition for Development of Nephropathy in Type 2 Diabetes Mellitus

The aim of the study was to explore the association of the angiotensin-converting enzyme (ACE) gene I/D polymorphism and the methylenetetrahydrofolate reductase (MTHFR) gene C677T polymorphism with development of diabetic nephropathy in type 2 diabetes mellitus. Three groups were recruited during 2007–2011: 232 normal controls, 185 type 2 diabetics without nephropathy, and 407 type 2 diabetics with nephropathy. The ACE I/D and MTHFR C677T polymorphisms were examined using PCR and PCR-RFLP methods. We found no significant association of the ACE I/D polymorphism with diabetic nephropathy in genotype, allele, dominant, and recessive models. We observed a significant association of MTHFR C677T with development of diabetic nephropathy in type 2 diabetics. The MTHFR C677T polymorphism plays a significant role in predisposition of renal insufficiency in diabetic patients.     

A unified framework for the restoration of Southeast Asian mangroves—bridging ecology, society and economics

The effect of intensive human intervention, poor socio-economic conditions and little knowledge on mangrove ecology pose enormous challenges for mangrove restoration in Southeast Asia. We present a framework for tropical mangrove restoration. Our proposed restoration framework addresses the ecology, economy and social issues simultaneously by considering the causes of mangrove degradation. We provide a step by step guideline for its restoration. We argue that although, ecological issues are of prime importance, economic and social issues must be considered in the restoration plan in order for it to be successful. Since mangrove ecology is not adequately studied in this region, local ecological knowledge can be used to fill the baseline information gaps. Unwanted human disturbance can be minimized by encouraging community participation. This can be ensured and sustained by facilitating the livelihood of the coastal community. We translated the restoration paradigm into a readily available practical guideline for the executors of the plans. We provide an example of mangrove restoration project that is closely related to our proposed framework. We are optimistic that this framework has the potential for universal application with necessary adjustments.     

Nitric oxide alleviates manganese toxicity by preventing oxidative stress in excised rice leaves

In the present study, we have investigated the effects of nitric oxide (NO) on alleviating manganese (Mn)-induced oxidative stress in rice leaves. Exogenous MnCl₂ treatment to excised rice leaves for 24 and 48 h resulted in increased production of H₂O₂ and lipid peroxides, decline in the levels of antioxidants, glutathione and ascorbic acid, and increased activities of antioxidative enzymes, superoxide dismutase, guaiacol peroxidase, catalase, ascorbate peroxidase, dehydroascorbate reductase, and glutathione reductase. Treatment of rice leaves with 100 μM sodium nitroprusside (SNP), a NO donor, was effective in reducing Mn-induced increased levels of H₂O₂, lipid peroxides and increased activities of antioxidative enzymes. The levels of reduced ascorbate and glutathione were considerably recovered due to SNP treatment. The effect of SNP was reversed by the addition of NO scavenger, 2-(4-carboxy-2-phenyl)-4,4,5,5-tetramethyl-imidazoline-1-oxyl-3-oxide (c-PTIO) suggesting that ameliorating effect of SNP is due to release of NO. The results indicate that MnCl₂ induces oxidative stress in excised rice leaves, lowers the levels of reduced ascorbate and glutathione, and elevates activities of the key antioxidative enzymes. NO appears to provide a protection to the rice leaves against Mn-induced oxidative stress and that exogenous NO application could be advantageous in combating the deleterious effects of Mn-toxicity in rice plants.     

Role of the Substrate Specificity-Defining Residues of Human SIRT5 in Modulating the Structural Stability and Inhibitory Features of the Enzyme

Sirtuins are emerging as the key regulators of metabolism and aging, and their potential activators and inhibitors are being explored as therapeutics for improving health and treating associated diseases. Despite the global structural similarity among all seven isoforms of sirtuins (of which most of them catalyze the deacetylation reaction), SIRT5 is the only isoform that catalyzes the cleavage of negatively charged acylated substrates, and the latter feature appears to be encoded by the presence of Tyr102 and Arg105 residues at the active site pocket of the enzyme. To determine the contributions of the above residues in SIRT5 (vis a vis the corresponding residues of SIRT1) on substrate selectivity, inhibition by EX527 and nicotinamide, secondary structural features and thermal stability of the enzymes, we created single and double mutations (viz. Y102A, R105l, and Y102A/R105I) in SIRT5. The kinetic data revealed that while Y102A mutant enzyme catalyzed both deacetylation and desuccinylation reactions with comparable efficiencies, R105I and Y102A/R105I mutant enzymes favored the deacetylase reaction. Like SIRT1, the nicotinamide inhibition of SIRT5 double mutant (Y102A/R105I) exhibited the mixed non-competitive behavior. On the other hand, the desuccinylation reaction of both wild-type and Y102A mutant enzymes conformed to the competitive inhibition model. The inhibitory potency of EX527 progressively increased from Y102A, R105I, to Y102A/R105 mutant enzymes in SIRT5, but it did not reach to the level obtained with SIRT1. The CD spectroscopic data for the wild-type and mutant enzymes revealed changes in the secondary structural features of the enzymes, and such changes were more pronounced on examining their thermal denaturation patterns. A cumulative account of our experimental data reveal mutual cooperation between Y102 and R105 residues in promoting the desuccinylation versus deacetylation reaction in SIRT5, and the overall catalytic feature of the enzyme is manifested via the mutation induced modulation in the protein structure.     

Synthesis of silver nanoparticles by Bacillus clausii and computational profiling of nitrate reductase enzyme involved in production

Biogenic synthesis of silver nanoparticles using microorganisms has found interest recently since last decade because of their prospect to synthesize nanoparticles of various size, shape and morphology which are eco-friendly. Here, an eco-friendly method for production of silver nanoparticles from Bacillus clausii cultured from Enterogermina is explored. Along with the biosynthesis and conformity test, in silico studies was done on NADPH dependent nitrate reductase enzymes from the view point of designing a rational enzymatic strategy for the synthesis. The detailed characterization of the nanoparticles was carried out using UV-Vis spectroscopy, Dynamic Light Scattering (DLS) particle size analysis, Transmission Electron Microscopy (TEM), X-Ray Diffraction (XRD) analysis. Computational profiling and in silico characterization of NADH dependent enzymes was carried out based on literature and work done so far. Nitrate reductase sequence was retrieved from NCBI for characterization. Secondary structure was evaluated and verified by JPred as well as SOPMA Tool. Tertiary structure was also modeled by MODELLER and ITASSER parallel and the best structure was selected based on energy values. Structure validation was done by GROMACS and RMSD, RMSF, temperature variation plot were also plotted. Interactions graphs between nitrate reductase and ligand silver nitrate was done through molecular docking using Hex.     

Relationship of Parental Genetic Distance with Heterosis and Specific Combining Ability in Sesame (<Emphasis Type="Italic">Sesamum indicum</Emphasis> L.) Based on Phenotypic and Molecular Marker Analysis

The genetic distance analysis for selection of suitable parents has been established and effectively used in many crops; however, there is dearth of conclusive report of relationship of genetic distance analysis with heterosis in sesame. In the present study, an attempt was made to estimate the associations of genetic distances using SSR (GDSSR), seed-storage protein profiling (GDSDS) and agro-morphological traits (GDMOR) with hybrid performance. Seven parents were selected from 60 exotic and Indian genotypes based on genetic distance from clustering pattern based on SSR, seed-storage protein, morphological traits and per se performance. For combining ability analysis, 7 parents and 21 crosses generated from 7 × 7 half diallel evaluated at two environments in a replicated field trial during pre-kharif season of 2013. Compared with the average parents yield (12.57 g plant^?1), eight hybrids had a significant (P < 0.01) yield advantage across environments, with averages of 26.94 and 29.99% for better-parent heterosis (BPH) and mid-parent heterosis (MPH), respectively, across environments. Highly significant positive correlation was observed between specific combining ability (SCA) and per se performance (0.97), while positive non-significant correlation of BPH with GDSSR (0.048), and non-significant negative correlations with GDMOR (? 0.01) and GDSDS (? 0.256) were observed. The linear regressions of SCA on MPH, BPH and per se performance of F₁s were significant with R² value of 0.88, 0.84 and 0.95 respectively. The present findings revealed a weak association of GDSSR with F₁’s performance; however, SCA has appeared as an important factor in the determination of heterosis and per se performance of the hybrids. The present findings also indicated that parental divergence in the intermediate group would likely produce high heterotic crosses in sesame.     

Identification of gene signatures from RNA-seq data using Pareto-optimal cluster algorithm

Background

Gene signatures are important to represent the molecular changes in the disease genomes or the cells in specific conditions, and have been often used to separate samples into different groups for better research or clinical treatment. While many methods and applications have been available in literature, there still lack powerful ones that can take account of the complex data and detect the most informative signatures.

Methods

In this article, we present a new framework for identifying gene signatures using Pareto-optimal cluster size identification for RNA-seq data. We first performed pre-filtering steps and normalization, then utilized the empirical Bayes test in Limma package to identify the differentially expressed genes (DEGs). Next, we used a multi-objective optimization technique, “Multi-objective optimization for collecting cluster alternatives” (MOCCA in R package) on these DEGs to find Pareto-optimal cluster size, and then applied k-means clustering to the RNA-seq data based on the optimal cluster size. The best cluster was obtained through computing the average Spearman’s Correlation Score among all the genes in pair-wise manner belonging to the module. The best cluster is treated as the signature for the respective disease or cellular condition.

Results

We applied our framework to a cervical cancer RNA-seq dataset, which included 253 squamous cell carcinoma (SCC) samples and 22 adenocarcinoma (ADENO) samples. We identified a total of 582 DEGs by Limma analysis of SCC versus ADENO samples. Among them, 260 are up-regulated genes and 322 are down-regulated genes. Using MOCCA, we obtained seven Pareto-optimal clusters. The best cluster has a total of 35 DEGs consisting of all-upregulated genes. For validation, we ran PAMR (prediction analysis for microarrays) classifier on the selected best cluster, and assessed the classification performance. Our evaluation, measured by sensitivity, specificity, precision, and accuracy, showed high confidence.

Conclusions

Our framework identified a multi-objective based cluster that is treated as a signature that can classify the disease and control group of samples with higher classification performance (accuracy 0.935) for the corresponding disease. Our method is useful to find signature for any RNA-seq or microarray data.