The genetic association study of TP53 polymorphisms in Saudi obese patients

Obesity is a multifactorial metabolic disorder characterized by low grade chronic inflammation. Rare and novel mutations in genes which are vital in several key pathways have been reported to alter the energy expenditure which regulates body weight. The TP53 or p53 gene plays a prominent role in regulating various metabolic activities such as glycolysis, lipolysis, and glycogen synthesis. Recent genome-wide association studies reported that tumor suppressor gene p53 variants play a critical role in the predisposition of type 2 diabetes and obesity. Till date, no reports are available from the Arabian population; hence the present study was intended to assess the association between p53 variants with risk of obesity development in the Saudi population. We have selected three p53 polymorphisms, rs1642785 (C > G), and rs9894946 (A > G), and rs1042522 (Pro72Arg; C > G) and assessed their association with obesity risk in the Saudi population. Phenotypic and biochemical parameters were also evaluated to check their association with p53 genotypes and obesity. Genotyping was carried out on 136 obese and 122 normal samples. We observed that there is significantly increased prevalence p52 Pro72Arg (rs1042522) polymorphism in obese persons when compared to controls at GG genotype in overall comparison (OR: 2.169, 95% CI: 1.086-4.334, p = 0.02716). Male obese subjects showed three-fold higher risk at GG genotype (OR: 3.275, 95% CI: 1.230-8.716, p = 0.01560) and two-fold risk at G allele (OR: 1.827, 95% CI: 1.128-2.958, p = 0.01388) of p53 variant Pro72Arg respectively. This variant has also shown significant influence on cholesterol, LDL level, and random insulin levels in obese subjects (p ≤ 0.05). In conclusion, p53 Pro72Arg variant is highly prevalent among obese individuals and may act as a genetic modifier for obesity development among Saudis.     

Capacity optimization and scheduling of a multiproduct manufacturing facility for biotech products

A general mathematical framework has been proposed in this work for scheduling of a multiproduct and multipurpose facility involving manufacturing of biotech products. The specific problem involves several batch operations occurring in multiple units involving fixed processing time, unlimited storage policy, transition times, shared units, and deterministic and fixed data in the given time horizon. The different batch operations are modeled using state‐task network representation. Two different mathematical formulations are proposed based on discrete‐ and continuous‐time representations leading to a mixed‐integer linear programming model which is solved using General Algebraic Modeling System software. A case study based on a real facility is presented to illustrate the potential and applicability of the proposed models. The continuous‐time model required less number of events and has a smaller problem size compared to the discrete‐time model. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1221–1230, 2014     

Comparative modeling of Rab6 proteins: identification of key residues and their interactions with guanine nucleotides

The cytoplasm of a eukaryotic cell consists of a wide variety of membrane bound cell organelles and continuous flow of proteins amongst these organelles is a major challenge and must be stringently maintained in order to continue the correct biochemical functioning inside a cell. The transportation of various proteins amongst these organelles is facilitated by a vast Tubulo-vesicular network mediated by carrier proteins. The Rabs belong to small G proteins super family involved in the regulation and vesicle transport in between the organelles by shuttling between the active GTP and inactive GDP bound states. In this paper we put forth the homology modeling and docking studies of Rab6A proteins (Mus musculus, Gallus gallus and Caenorhabditis elegans) with GTP, GMP-PNP and GDP molecules and a comparative study between these proteins is done to identify key residues out of which serine of the phosphate binding loop (P – loop) and aspartic acid showed prominent interactions with the GTP, GDP and GMP-PNP nucleotides and cogitate that aspartic acid might also help in the stabilization of the switch I region of the Rab proteins besides serine.     

Low plasma albumin levels are associated with increased plasma protein glycation and HbA1c in diabetes

Albumin is one of the most abundant plasma proteins and is heavily glycated in diabetes. In this study, we have addressed whether variation in the albumin levels influence glycation of plasma proteins and HbA1c. The study was performed in three systems: (1) streptozotocin (STZ)-induced diabetic mice plasma, (2) diabetic clinical plasma, and (3) in vitro glycated plasma. Diabetic mice and clinical plasma samples were categorized as diabetic high albumin plasma (DHAP) and diabetic low albumin plasma (DLAP) on the basis of their albumin levels. For the in vitro experiment, two albumin levels, high albumin plasma (HAP) and low albumin plasma (LAP), were created by differential depletion of plasma albumin. Protein glycation was studied by using a combination of two-dimensional electrophoresis (2DE), Western blotting, and LC-MS(E). In both mice and clinical experiments, an increased plasma protein glycation was observed in DLAP than in DHAP. Additionally, plasma albumin levels were negatively correlated with HbA1c. The in vitro experiment with differential depletion of albumin mechanistically showed that the low albumin levels are associated with increased plasma protein glycation and that albumin competes for glycation with other plasma proteins.     

HPLC and GC analyses of in vitro-grown leaves of the cancer bush <Emphasis Type="Italic">Lessertia</Emphasis> (<Emphasis Type="Italic">Sutherlandia</Emphasis>) <Emphasis Type="Italic">frutescens</Emphasis> L. reveal higher yields of bioactive compounds

Lessertia frutescens L., commonly known as cancer-bush, is a medicinally reputed plant species indigenous to southern Africa. Field leaf extracts of this species are known to exhibit many curative properties. However, little is known about the bioactive compounds that are present in in vitro leaf extracts and seed extracts. The objective of this study was to verify the presence of and quantify l-canavanine, gamma amino butyric acid (GABA), arginine and d-pinitol in the seeds, field leaves and in vitro leaves of L. frutescens using gas and liquid chromatography. Methanolic extracts of in vitro leaves, field leaves and seeds were used. MRM chromatograms were recorded for l-canavanine and arginine using tandem mass spectrometry. GC chromatograms were recorded for GABA and d-pinitol using gas chromatography. d-Pinitol was found to be most abundant and was 14.75 and 18.17 mg/g in in vitro and field leaf extracts respectively, followed by GABA (7.29 and 3.48 mg/g), arginine (7.08 and 0.35 mg/g) and l-canavanine (0.55 and 0.08 mg/g). In the seed extracts, GABA content was found to be the highest (1.69 mg/g) followed by l-canavanine (0.37 mg/g), then d-pinitol (0.25 mg/g), and arginine (0.02 mg/g). In vitro leaves had higher quantities of all compounds, except for d-pinitol. This study therefore highlights the potential of bulking in vitro leaves for the extraction of the medicinal compounds, l-canavanine and GABA.     

Molecular designing,virtual screening and docking study of novel curcumin analogue as mutation (S769L and K846R) selective inhibitor for EGFR

The somatic mutations in ATP binding cleft of the tyrosine kinase binding domain of EGFR are known to occur in 15–40% of non-small cell lung cancer (NSCLC) patients. Although first and second generation anti-EGFR inhibitors are widely used to treat these patients, their therapeutic efficacy is modest and often results in adverse effects or drug resistance. Therefore, there is a need to develop novel as well as safe anti-EGFR drugs. The rapid emergence of computational drug designing provided a great opportunity to both discover and predict the efficacy of novel EGFR inhibitors from plant sources. In the present study, we designed several chemical analogues of edible curcumin (CUCM) compound and assessed their drug likeliness, ADME and toxicity properties using a diverse range of advanced computational methods. We also have examined the structural plasticity and binding characteristics of EGFR wild-type and mutant forms (S769L and K846R) against ligand molecules like Gefitinib, native CUCM, and different CUCM analogues. Through multidimensional experimental approaches, we conclude that CUCM-36 ((1E,4Z,6E)-1-(3,4-Diphenoxyphenyl)-5-hydroxy-7-(4-hydroxy-3-phenoxyphenyl)-1,4,6-heptatrien-3-one) is the best anti-EGFR compound with high drug-likeness, ADME properties, and low toxicity properties. CUCM-36 compound has demonstrated better affinity towards both wild-type (ΔG is ?8.5?kcal/Mol) and mutant forms (V769L & K846R; ΔG for both is >?9.20?kcal/Mol) compared to natural CUCM and Gefitinib inhibitor. This study advises the future laboratory assays to develop CUCM-36 as a novel drug compound for treating EGFR positive non-small cell lung cancer patients.     

REDHORSE-REcombination and Double crossover detection in Haploid Organisms using next-geneRation SEquencing data

Background

Next-generation sequencing technology provides a means to study genetic exchange at a higher resolution than was possible using earlier technologies. However, this improvement presents challenges as the alignments of next generation sequence data to a reference genome cannot be directly used as input to existing detection algorithms, which instead typically use multiple sequence alignments as input. We therefore designed a software suite called REDHORSE that uses genomic alignments, extracts genetic markers, and generates multiple sequence alignments that can be used as input to existing recombination detection algorithms. In addition, REDHORSE implements a custom recombination detection algorithm that makes use of sequence information and genomic positions to accurately detect crossovers. REDHORSE is a portable and platform independent suite that provides efficient analysis of genetic crosses based on Next-generation sequencing data.

Results

We demonstrated the utility of REDHORSE using simulated data and real Next-generation sequencing data. The simulated dataset mimicked recombination between two known haploid parental strains and allowed comparison of detected break points against known true break points to assess performance of recombination detection algorithms. A newly generated NGS dataset from a genetic cross of Toxoplasma gondii allowed us to demonstrate our pipeline. REDHORSE successfully extracted the relevant genetic markers and was able to transform the read alignments from NGS to the genome to generate multiple sequence alignments. Recombination detection algorithm in REDHORSE was able to detect conventional crossovers and double crossovers typically associated with gene conversions whilst filtering out artifacts that might have been introduced during sequencing or alignment. REDHORSE outperformed other commonly used recombination detection algorithms in finding conventional crossovers. In addition, REDHORSE was the only algorithm that was able to detect double crossovers.

Conclusion

REDHORSE is an efficient analytical pipeline that serves as a bridge between genomic alignments and existing recombination detection algorithms. Moreover, REDHORSE is equipped with a recombination detection algorithm specifically designed for Next-generation sequencing data. REDHORSE is portable, platform independent Java based utility that provides efficient analysis of genetic crosses based on Next-generation sequencing data. REDHORSE is available at http://redhorse.sourceforge.net/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1309-7) contains supplementary material, which is available to authorized users.     

Imidacloprid impedes mitochondrial function and induces oxidative stress in cotton bollworm, <Emphasis Type="Italic">Helicoverpa armigera</Emphasis> larvae (Hubner: Noctuidae)

Neonicotinoids have high agonistic affinity to insect nicotinic acetylcholine receptors (nAChR) and are frequently used as insecticides against most devastating lepidopteran insect pests. Imidacloprid influenced dose-dependent decline in the state III and IV respiration, respiration control index (RCI), and P/O ratios, in vitro and in vivo. The bioassay indicated its LD₅₀ value to be 531.24 μM. The insecticide exhibited a dose-dependent inhibition on F₀F₁-ATPase and complex IV activity. At 600 μM, the insecticide inhibited 83.62 and 27.13% of F₀F₁-ATPase and complex IV activity, respectively, and induced the release of 0.26 nmoles/min/mg protein of cytochrome c. A significant dose- and time-dependent increase in oxidative stress was observed; at 600 μM, the insecticide correspondingly induced lipid peroxidation, LDH activity, and accumulation of H₂O₂ content by 83.33, 31.51 and 223.66%. The stress was the maximum at 48 h of insecticide treatment (91.58, 35.28, and 189.80%, respectively). In contrast, catalase and superoxide dismutase were reduced in a dose- and time-dependent manner in imidacloprid-fed larvae. The results therefore suggest that imidacloprid impedes mitochondrial function and induces oxidative stress in H. armigera, which contributes to reduced growth of the larvae along with its neurotoxic effect.     

Competitive interactions between entomopathogenic nematodes and parasitoid venom

Entomopathogenic nematodes and parasitoid larvae of some wasps play important roles in the natural control of the pest insects. However, it has not been excluded that competition between nematodes and wasps may in some cases reduce their efficacy in the pest control. Using caterpillars of Spodoptera littoralis, we examined interactions between the nematode Steinernema carpocapsae and the venom of the parasitoid Habrobracon hebetor. The survival of S. littoralis caterpillars was reduced in a dose-dependent manner when 5 to 500 nematodes or 0.005–0.1 venom units were applied to single caterpillars. High doses of either nematodes or the venom caused death within 1–3 days in all treated hosts. The low doses of nematodes killed caterpillars within a week, in some cases when they attempted to pupate. Caterpillars receiving low venom doses were characterized by extended survival time terminated with death due to starvation. Combined treatment of nematodes and the venom were mutually synergistic and elicited severe lethal effects. The nematodes were fully resistant to the venom and can feed and grow on the symbiotic bacteria in vitro. The venom impairs food processing and causes death of caterpillars due to starvation. Disruption of the hormonal regulation of metamorphosis by ecdysteroids and juvenile hormone could be responsible for defective moults block at different stages of the moulting process, regionally restricted moulting, moults to “intermediates” combining regions of newly secreted larval and pupal cuticles.     

QSAR studies on the activation of the human carbonic anhydrase cytosolic isoforms I and II and secretory isozyme VI with amino acids and amines

The first QSAR study on the activation of the human secretory isoform of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1), CA VI, with a series of amines and amino acids is reported. A large set of topological indices have been used to obtain several tri-/tetra-parametric models. We compared the CA VI activating QSAR models with those calculated for activation of the cytosolic human isozymes hCA I and hCA II. In addition, the effect of D- and L-amino acids as activators of hCA I, hCA II and of hCA VI as compared to those of structurally related biogenic amines was investigated for obtaining statistically significant and predictive QSAR equations. The obtained models are discussed using a variety of statistical parameters. The best models were obtained for hCA II activation, followed by hCA I, whereas the QSAR models for the activation of hCA VI were statistically weaker.