GSK3 inhibitors stabilize Wee1 and reduce cerebellar granule cell progenitor proliferation

Ubiquitin mediated proteolysis is required for transition from one cell cycle phase to another. For instance, the mitosis inhibitor Wee1 is targeted for degradation during S phase and G2 to allow mitotic entry. Wee1 is an essential tyrosine kinase required for the G2/M transition and S-phase progression. Although several studies have concentrated on Wee1 regulation during mitosis, few have elucidated its degradation during interphase. Our prior studies have demonstrated that Wee1 is degraded via CK1δ dependent phosphorylation during the S and G2/M phases of the cell cycle. Here we demonstrate that GSK3β may work in concert with CK1δ to induce Wee1 destruction during interphase. We generated small molecules that specifically stabilized Wee1. We profiled these compounds against 296 kinases and found that they inhibit GSK3α and GSK3β, suggesting that Wee1 may be targeted for proteolysis by GSK3. Consistent with this notion, known GSK3 inhibitors stabilized Wee1 and GSK3β depletion reduced Wee1 turnover. Given Wee1''s central role in cell cycle progression, we predicted that GSK3 inhibitors should limit cell proliferation. Indeed, we demonstrate that GSK3 inhibitors potently inhibited proliferation of the most abundant cell in the mammalian brain, the cerebellar granule cell progenitor (GCP). These studies identify a previously unappreciated role for GSK3β mediated regulation of Wee1 during the cell cycle and in neurogenesis. Furthermore, they suggest that pharmacological inhibition of Wee1 may be therapeutically attractive in some cancers where GSK-3β or Wee1 are dysregulated.     

Immobilization of microbial cells on inner epidermis of onion bulb scale for biosensor application

Inner epidermis of onion bulb scales was used as a natural support for immobilization of microbial cells for biosensor application. A bacterium Sphingomonas sp. that hydrolyzes methyl parathion into a chromophoric product, p-nitrophenol (PNP), has been isolated and identified in our laboratory. PNP can be detected by electrochemical and colorimetric methods. Whole cells of Sphingomonas sp. were immobilized on inner epidermis of onion bulb scale by adsorption followed by cross-linking methods. Cells immobilized onion membrane was directly placed in the wells of microplate and associated with the optical transducer. Methyl parathion is an organophosphorus pesticide that has been widely used in the field of agriculture for insect pest control. This pesticide causes environmental pollution and ecological problem. A detection range 4-80 μM of methyl parathion was estimated from the linear range of calibration plot of enzymatic assay. A single membrane was reused for 52 reactions and was found to be stable for 32 days with 90% of its initial hydrolytic activity. The applicability of the cells immobilized onion membrane was also demonstrated with spiked samples.     

Bioassay to detect <Emphasis Type="Italic">Ascophyllum nodosum</Emphasis> extract-induced cytokinin-like activity in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>

Ascophyllum nodosum, a brown macroalga, is the most widely used seaweed in agriculture. We report a rapid method for the detection of cytokinin-like activity in plants treated with a commercial A. nodosum liquid concentrate (Stimplex®) using a transgenic line of Arabidopsis carrying the ARR5 promoter fused to ß-glucuronidase (GUS) reporter gene. Based on GUS activity assay, an increase in cytokinin-like activity was detected in plants grown in vitro treated with 3 mL L^?1 Stimplex®, whereas foliar spray treatments showed similar cytokinin-like activity at a concentration of 5 mL L^?1. Histochemical staining showed Stimplex®-induced GUS activity in leaf as well as in the root tissues. Taken together, our results suggest that Stimplex® contains compounds that may elicit endogenous cytokinin-like activity. Furthermore, it is shown that this bioassay can be used for rapid screening of extracts that can stimulate cytokinin-like activities using Arabidopsis AAR5::GUS reporter transgenic plants.     

Ability to use the diazo dye, C.I. Acid Black 1 as a nitrogen source by the marine cyanobacterium Oscillatoria curviceps BDU92191

Ten different strains of marine cyanobacteria were tested for their ability to decolourise and degrade a recalcitrant diazo dye, C.I. Acid Black 1. Of them, Oscillatoria curvicepsBDU92191 was able to grow up to a tested concentration of 500 mG L⁻¹. The organism degraded 84% of the dye at 100 mG L⁻¹ in 8 days in a medium free of combined nitrogen. The dye degrading ability is attributed to the activities of the enzymes: laccase, polyphenol oxidase and azoreductase. The absence of the doublet amine peak in addition to the overall reduction of absorption in the IR spectra confirmed the mineralisation of the tested azo dye. The nitrogen assimilating enzyme studies along with nitrogenase assay strongly suggested the ability of the non-heterocystous, filamentous marine cyanobacterium, O. curvicepsBDU92191 to use C.I. Acid Black 1 as a nitrogen source in an oligotrophic environment.     

Learning generative models for protein fold families

We introduce a new approach to learning statistical models from multiple sequence alignments (MSA) of proteins. Our method, called GREMLIN (Generative REgularized ModeLs of proteINs), learns an undirected probabilistic graphical model of the amino acid composition within the MSA. The resulting model encodes both the position-specific conservation statistics and the correlated mutation statistics between sequential and long-range pairs of residues. Existing techniques for learning graphical models from MSA either make strong, and often inappropriate assumptions about the conditional independencies within the MSA (e.g., Hidden Markov Models), or else use suboptimal algorithms to learn the parameters of the model. In contrast, GREMLIN makes no a priori assumptions about the conditional independencies within the MSA. We formulate and solve a convex optimization problem, thus guaranteeing that we find a globally optimal model at convergence. The resulting model is also generative, allowing for the design of new protein sequences that have the same statistical properties as those in the MSA. We perform a detailed analysis of covariation statistics on the extensively studied WW and PDZ domains and show that our method out-performs an existing algorithm for learning undirected probabilistic graphical models from MSA. We then apply our approach to 71 additional families from the PFAM database and demonstrate that the resulting models significantly out-perform Hidden Markov Models in terms of predictive accuracy.     

Structure based drug designing of a novel antiflaviviral inhibitor for nonstructural 3 protein

Literature shows that Flaviviruses cause a variety of diseases, including fevers, encephalitis, and hemorrhagic fevers. NS3 is a multifunctional protein with an Nterminal protease domain (NS3pro) that is responsible for proteolytic processing of the viral polyprotein, and a C-terminal region that contains an RNA triphosphatase, RNA helicase and RNA-stimulated NTPase domain that are essential for RNA replication. Therefore, NS3 protein is the preferential choice for inhibition to stop the proteolytic processing. Hence, the 3D structure of NS3 protein was modeled using homology modeling by MODELLER 9v7. Evaluation of the constructed NS3 protein models were done by PROCHECK, VERYFY3D and through ProSA calculations. Ligands for the catalytic triad were designed using LIGBUILDER. The NS3 protein's catalytic triad was explored to find out the critical interactions pattern for inhibitor binding using molecular docking methodology using AUTODOCK Vina. It should be noted that these predicted data should be validated using suitable assays for further consideration. ABBREVIATIONS: DOPE - Discrete optimized protein energy, WHO - World Health Organization, ADME/T - Absorption, Distribution, Metabolism, Excretion and Toxicity.     

Insights from the analysis of conserved motifs and permitted amino acid exchanges in the human, the fly and the worm GPCR clusters

G-protein coupled receptors (GPCRs) belong to biologically important and functionally diverse and largest super family of membrane proteins. GPCRs retain a characteristic membrane topology of seven alpha helices with three intracellular, three extracellular loops and flanking N' and C' terminal residues. Subtle differences do exist in the helix boundaries (TM-domain), loop lengths, sequence features such as conserved motifs, and substituting amino acid patterns and their physiochemical properties amongst these sequences (clusters) at intra-genomic and inter-genomic level (please re-phrase into 2 statements for clarity). In the current study, we employ prediction of helix boundaries and scores derived from amino acid substitution exchange matrices to identify the conserved amino acid residues (motifs) as consensus in aligned set of homologous GPCR sequences. Co-clustered GPCRs from human and other genomes, organized as 32 clusters, were employed to study the amino acid conservation patterns and species-specific or cluster-specific motifs. Critical analysis on sequence composition and properties provide clues to connect functional relevance within and across genome for vast practical applications such as design of mutations and understanding of disease-causing genetic abnormalities.     

Identification of hub proteins from sequence

Identification of hub proteins from sequence is a challenge in molecular biology. Therefore, it is of interest to predict protein hubs in networks. We describe the prediction of protein "hub" using physiochemical, thermodynamic and conformational properties of amino acid residues in sequence. We have used twenty sequence based features to identify hub behaviour. Linear discriminant analysis and normalised Bayesian approach were utilized for identifying hub proteins solely using these sequence features in E. coli/H. sapiens datasets with accuracies of 99.5/98.6, 87.8/89.6 and 90.1/92.6, respectively.     

Assessment of Polycyclic Aromatic Hydrocarbons (PAH) and Heavy Metals in the Vicinity of an Oil Refinery in India

Petroleum products are one of the major sources of energy for industry and daily life. Growth of the petroleum industry and shipping of petroleum products has resulted in the pollution. Populations living in the vicinity of oil refinery waste sites may be at greater risk of potential exposure to polycyclic aromatic hydrocarbons (PAH) through inhalation, ingestion, and direct contact with contaminated media. PAH have often been found to coexist with environmental pollutants including heavy metals due to similar pollution sources. The levels and distribution patterns of Σ16 PAH (sum of the 16 PAH) and heavy metals (lead, copper, nickel, cobalt, and chromium) were determined in soil and sediment in the vicinity (5 km radius) of an oil refinery in India. Concentrations of Σ16 PAH in the soils and sediments were found to be 60.36 and 241.23 ppm, respectively. Higher amount of PAH in sediments as compared to soil is due to low water solubility of PAH, settled in the bottom of aquatic bodies. The levels of lead, copper, nickel, cobalt, and chromium (total) in soil were 12.52, 13.52, 18.78, 4.84, and 8.29 ppm, while the concentrations of these metals in sediments were 16.38, 47.88, 50.15, 7.07, and 13.25 ppm, respectively. Molecular diagnostics indices of PAH (Ratio of Phenanthrene/Anthracene, Fluranthene/Pyrene) calculated for soil and sediment samples indicate that the oil refinery environment is contaminated with PAH from petrogenic as well as pyrolytic origin and heavy vehicular traffic on the Agra- Delhi National highway. Sixteen PAH priority pollutants were detected in the United States in entire samples collected near oil refinery areas and concentrations of Σ16 PAH in soil was found to be 1.20 times higher than the threshold value for PAH in soil by ICRCL (Inter-Departmental Committee on the Redevelopment of Contaminated Land). This concentration could lead to disastrous consequences for the biotic and abiotic components of the ecosystem and may affect the soil quality, thus impairing plant growth and its bioaccumulation in food chain.     

Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ~80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ~250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.