Arsenate Resistant Penicillium Coffeae: A Potential Fungus for Soil Bioremediation

Bioremediation is an effective method for the treatment of major metal contaminated sites. Fungi were isolated from soil samples collected from different arsenate contaminated areas across India. An isolate, Penicillium coffeae, exhibited resistance to arsenate up to 500 mM. Results indicated that pretreatment of biomass with alkali (NaOH) enhanced the percentage of adsorption to 66.8 % as compared to that of live and untreated dead biomass whose adsorption was 22.9 % and 60.2 % respectively. The physiological parameters evaluated in this study may help pilot studies aimed at bioremediation of arsenate contaminated effluents using arsenate resistant fungus P. coffeae

Complete Genome Sequence of Soil Fungus Aspergillus terreus (KM017963), a Potent Lovastatin Producer

We report the complete genome of Aspergillus terreus (KM017963), a tropical soil isolate. The genome sequence is 29 Mb, with a G+C content of 51.12%. The genome sequence of A. terreus shows the presence of the complete gene cluster responsible for lovastatin (an anti-cholesterol drug) production in a single scaffold (1.16)

Endophytic Fungi: A Poor Candidate for the Production of Lovastatin

Aim: The aim of the present study was to screen soil and endophytic fungi for production oflovastatin.Methodology: Soil fungi were isolated by dilution plating technique and endophytic fungi from selected medicinal plants by using standard procedures. All isolates were tested for lovastatin production by Solid State Fermentation (SSF) using wheat bran as substrate.Results: The soil isolate, Aspergillus terreus NCBI (KM017963) showed positive for lovastatin (1.0 mg/G DWS) whereas none of the endophytic fungi tested showedpositivefor lovastatin production

Lovastatin Production by Aspergillus terreus (KM017963) in Submerged and Solid State Fermentation: A Comparative Study

Lovastatin (C24H36O5) is a fungal secondary metabolite that inhibits conversion of 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) to mevalonate in cholesterol biosynthesis. Lovastatin producing fungus Aspergillus terreus was grown in Solid State Fermentation (SSF) with various agro based wastes and in Submerged Fermentation (SmF) to evaluate the suitable growth medium for maximum production of lovastatin. Eighty three agro based substrates and six different types of SmF media were used for the production. Wheat bran and sprouted wheat were suitable substrates for lovastatin production yielding1.00 mg/G DWS and 1.311 mg/DWS of lovastatin, respectively. None of the SmF medium was found to be suitable for lovastatin production, although all media supported growth of the fungus

Comparative Study on Whole Genome Sequences of Aspergillus terreus (Soil Fungus) and Diaporthe ampelina (Endophytic Fungus) with Reference to Lovastatin Production

Lovastatin is a competitive inhibitor of the enzyme hydroxymethyl glutaryl coenzyme A reductase (HMGR) in cholesterol biosynthetic pathway and hence used in the treatment of hyperlipidemia. In a previous study, we report a tropical soil isolate, Aspergillus terreus (KM017963), which produces ample amount of lovastatin than its counterpart that are endophytic in origin. Bioinformatic analysis of whole genome sequence of A. terreus (AH007774.1), a soil isolate revealed the presence of gene cluster (AF141924.1 & AF141925.1) responsible for lovastatin production, whereas endophytic fungi including a strain of A. terreus showed no homology with the lovastatin gene cluster. The molecular study was also carried out targeting PCR amplification of the two important genes, lovE (a regulatory gene) and lovF (transcriptional regulatory factor) in genomic and c-DNA of soil and endophytic fungi. Expression of the two genes was successful in A. terreus (KM017963), whereas the same was not achieved in endophytic fungi. To further validate our above findings, in the present study, the whole genome sequencing of A. terreus and a selected endophytic fungus, Diaporthe ampelina (Phomopsis) was performed. Lovastatin gene cluster, when aligned on the consensus sequence of both genomes, the entire lovastatin gene cluster was detected in a single scaffold (1.16) of A.terreus genome. On the contrary, there was a complete absence of lovastatin gene cluster in the genome of D. ampelina (an endophyte). The probable reasons for the absence of lovastatin gene cluster in endophytic fungi are discussed

Arsenate resistant penicillium coffeae: A potential fungus for soil bioremediation

Bioremediation is an effective method for the treatment of major metal contaminated sites. Fungi were isolated from soil samples collected from different arsenate contaminated areas across India. An isolate, Penicillium coffeae, exhibited resistance to arsenate up to 500 mM. Results indicated that pretreatment of biomass with alkali (NaOH) enhanced the percentage of adsorption to 66.8 as compared to that of live and untreated dead biomass whose adsorption was 22.9 and 60.2 respectively. The physiological parameters evaluated in this study may help pilot studies aimed at bioremediation of arsenate contaminated effluents using arsenate resistant fungus P. coffeae. © 2014 Springer Science+Business Media New York

Enhancing Impulsive Hatred Detection with Ensemble Techniques and Active Learning

The increasing propagation in recent years of hatred on social media and the dire requirement for counter measures have drawn critical speculation from state run administrations, organizations, and analysts. Despite the fact that specialists have observed that disdain is an issue across different Social media stages, there is an absence of models for online disdain location utilizing this multi-stage information. Different techniques have been produced for robotizing disdain discovery on the web. Here we will begin by giving the current issue that comes the right to speak freely of discourse on the Internet and the abuse of virtual entertainment stages like Twitter, as well as distinguishing the holes present in the current works. At long last, figured out how to tackle these issues. It is a considerably more testing task, as examination of the language in the common datasets shows that disdain needs one of a kind, discriminative highlights and in this manner making it challenging to find. Removing a few exceptional and significant elements and joining them in various sets to look at and dissect the presentation of different machine learning classification calculations as to each list of capabilities. At long last, subsequent to leading a top to bottom investigation, results show that it is feasible to fundamentally expand the classification score acquired