Lumbricus terrestris L. does not impact on the remediation efficiency of compost and biochar amendments

The aim of this study was to test the impact of compost and Biochar, with or without earthworms, on the mobility and availability of metals, and on the growth of grass to re-vegetate contaminated soil from the Parys Mountain mining site, Anglesey. We also determined if the addition of earthworms compromises remediation efforts. In a laboratory experiment, contaminated soil (1343 mg Cu kg−1, 2511 mg Pb kg−1 and 262 mg Zn kg−1) was remediated with compost and/or Biochar. After 77 days Lumbricus terrestris L. earthworms were added to the treatment remediated with both compost and Biochar, and left for 28 days. L. terrestris was not able to survive in the Biochar, compost or unamended treatments. A germination and growth bioassay, using Agrostis capillaris (Common Bent) was then run on all treatments for 28 days. The combination of Biochar and compost decreased water soluble Cu (from 5.6 to 0.2 mg kg−1), Pb (0.17 to less than 0.007 mg kg−1) and Zn (3.3 to 0.05 mg kg−1) in the contaminated soil and increased the pH from 2.7 to 6.6. The addition of L. terrestris to this treatment had no effect on the concentration of the water soluble metals in the remediated soil. The compost was the only treatment that resulted in germination and growth of A. capillaris suitable for re-vegetation purposes. However, the combination of compost, Biochar (with or without L. terrestris) produced the lowest concentrations of Cu (8 mg kg−1) and Zn (36 mg kg−1) in the aboveground biomass, lower than the compost treatment (15 mgCu kg−1 and 126 mgZn kg−1). The addition of Biochar and compost both separately and as co-amendments was effective in reducing the mobility and availability of metals. The addition of L. terrestris did not re-mobilise previously sequestered metals.

Efficiency of pseudo-spectral algorithms with Anderson mixing for the SCFT of periodic block-copolymer phases

This study examines the numerical accuracy, computational cost, and memory requirements of self-consistent field theory (SCFT) calculations when the diffusion equations are solved with various pseudo-spectral methods and the mean field equations are iterated with Anderson mixing. The different methods are tested on the triply-periodic gyroid and spherical phases of a diblock-copolymer melt over a range of intermediate segregations. Anderson mixing is found to be somewhat less effective than when combined with the full-spectral method, but it nevertheless functions admirably well provided that a large number of histories is used. Of the different pseudo-spectral algorithms, the 4th-order one of Ranjan, Qin and Morse performs best, although not quite as efficiently as the full-spectral method.

Analysis of protein networks in resting and collagen receptor (GPVI)-stimulated platelet sub-proteomes.

Proteomics approaches have made important contributions to the characterisation of platelet regulatory mechanisms. A common problem encountered with this method, however, is the masking of low-abundance (e.g. signalling) proteins in complex mixtures by highly abundant proteins. In this study, subcellular fractionation of washed human platelets either inactivated or stimulated with the glycoprotein (GP) VI collagen receptor agonist, collagen-related peptide, reduced the complexity of the platelet proteome. The majority of proteins identified by tandem mass spectrometry are involved in signalling. The effect of GPVI stimulation on levels of specific proteins in subcellular compartments was compared and analysed using in silico quantification, and protein associations were predicted using STRING (the search tool for recurring instances of neighbouring genes/proteins). Interestingly, we observed that some proteins that were previously unidentified in platelets including teneurin-1 and Van Gogh-like protein 1, translocated to the membrane upon GPVI stimulation. Newly identified proteins may be involved in GPVI signalling nodes of importance for haemostasis and thrombosis.

The DISOPRED server for the prediction of protein disorder

Dynamically disordered regions appear to be relatively abundant in eukaryotic proteomes. The DISOPRED server allows users to submit a protein sequence, and returns a probability estimate of each residue in the sequence being disordered. The results are sent in both plain text and graphical formats, and the server can also supply predictions of secondary structure to provide further structural information.

The role of protein hydrophobicity in thionin–phospholipid interactions: a comparison of α1 and α2-purothionin adsorbed anionic phospholipid monolayers

The plant defence proteins α1- and α2-purothionin (Pth) are type 1 thionins from common wheat (Triticum aestivum). These highly homologous proteins possess characteristics common amongst antimicrobial peptides and proteins, that is, cationic charge, amphiphilicity and hydrophobicity. Both α1- and α2-Pth possess the same net charge, but differ in relative hydrophobicity as determined by C18 reversed phase HPLC. Brewster angle microscopy, X-ray and neutron reflectometry, external reflection FTIR and associated surface pressure measurements demonstrated that α1 and α2-Pth interact strongly with condensed phase 1,2-dipalmitoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DPPG) monolayers at the air/liquid interface. Both thionins disrupted the in-plane structure of the anionic phospholipid monolayer, removing lipid during this process and both penetrated the lipid monolayer in addition to adsorbing as a single protein layer to the lipid head-group. However, analysis of the interfacial structures revealed that the α2-Pth showed faster disruption of the lipid film and removed more phospholipid (12%) from the interface than α1-Pth. Correlating the protein properties and lipid binding activity suggests that hydrophobicity plays a key role in the membrane lipid removal activity of thionins.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.