Cytotoxic cobalt (III) Schiff base complexes: in vitro anti-proliferative,oxidative stress and gene expression studies in human breast and lung cancer cells

BioMetals - Increasing cancer drug chemo-resistance, especially in the treatment of breast and lung cancers, alarms the immediate need of newer and effective anticancer drugs. Until now,...     

Improvement of antioxidant and defense properties of Tomato (var. Pusa Rohini) by application of bioaugmented compost

Nutrient management practices play a significant role in improving the nutritional quality of tomato. The present study deals with the evaluation of compost prepared using Effective Microorganisms (EM), on antioxidant and defense enzyme activities of Tomato (Lycopersicon esculentum). A field experiment with five treatments (control, chemical fertilizer and EM compost alone and in combination) was conducted in randomized block design. An increment of 31.83% in tomato yield was recorded with the combined use of EM compost and half recommended dose of chemical fertilizers (N₅₀P₃₀K₂₅ + EM compost at the rate of 5 t ha⁻¹). Similarly, fruit quality was improved in terms of lycopene content (35.52%), antioxidant activity (24–63%) and defense enzymes activity (11–54%), in tomatoes in this treatment as compared to the application of recommended dose of fertilizers. Soil microbiological parameters also exhibited an increase of 7–31% in the enzyme activities in this treatment. Significant correlation among fruit quality parameters with soil microbiological activities reveals the positive impact of EM compost which may be adopted as an eco-friendly strategy for production of high quality edible products.     

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.     

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.     

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.     

Head and neck lymphatic tumors and bony abnormalities: a clinical and molecular review

Lymphatic malformations and lymphatic-derived tumors commonly involve the head and neck, where they may be associated with bony abnormalities and other systemic symptoms. The reasons for the association between these disorders and local skeletal changes are largely unknown, but such changes may cause significant disease-related morbidity. Ongoing work in molecular and developmental biology is beginning to uncover potential reasons for the bony abnormalities found in head and neck lymphatic disease; this article summarizes current knowledge on possible mechanisms underlying this association.