Synthetic RNA Silencing of Actinorhodin Biosynthesis in Streptomyces coelicolor A3(2)

We demonstrate the first application of synthetic RNA gene silencers in Streptomyces coelicolor A3(2). Peptide nucleic acid and expressed antisense RNA silencers successfully inhibited actinorhodin production. Synthetic RNA silencing was target-specific and is a new tool for gene regulation and metabolic engineering studies in Streptomyces.Peer reviewe

nocoRNAc: Characterization of non-coding RNAs in prokaryotes

<p>Abstract</p> <p>Background</p> <p>The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.</p> <p>Results</p> <p>We present <smcaps>NOCO</smcaps>RNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. <smcaps>NOCO</smcaps>RNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and <smcaps>NOCO</smcaps>RNAc to the genome of <it>Streptomyces coelicolor </it>and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.</p> <p>Conclusions</p> <p>We have developed <smcaps>NOCO</smcaps>RNAc, a framework that facilitates the automated characterization of functional ncRNAs. <smcaps>NOCO</smcaps>RNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. <smcaps>NOCO</smcaps>RNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at <url>http://www.zbit.uni-tuebingen.de/pas/nocornac.htm</url>.</p

Machine learning on normalized protein sequences

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current methods is the inability to handle varying sequence lengths.</p> <p>Findings</p> <p>We propose to normalize sequences to uniform length. To this end, we tested one linear and four different non-linear interpolation methods for the normalization of sequence lengths of 19 classification datasets. Classification tasks included prediction of HIV-1 drug resistance from drug target sequences and sequence-based prediction of protein function. We applied random forests to the classification of sequences into "positive" and "negative" samples. Statistical tests showed that the linear interpolation outperforms the non-linear interpolation methods in most of the analyzed datasets, while in a few cases non-linear methods had a small but significant advantage. Compared to other published methods, our prediction scheme leads to an improvement in prediction accuracy by up to 14%.</p> <p>Conclusions</p> <p>We found that machine learning on sequences normalized by simple linear interpolation gave better or at least competitive results compared to state-of-the-art procedures, and thus, is a promising alternative to existing methods, especially for protein sequences of variable length.</p

Integrating anaerobic digestion and pyrolysis for treating digestates derived from sewage sludge and fat wastes

P. 32603-32614The coupling of biological and thermal technologies allows for the complete conversion of wastes into energy and biochar eliminating the problem of sludge disposal. The valorisation of fatty residues as co-substrate in a mesophilic digester of a wastewater treatment plant was studied considering an integrated approach of co-digestion and pyrolysis. Four digested samples obtained from co-digestion of sewage sludge and butcher’s fat waste were studied by thermogravimetric analysis. The activation energy corresponding to the sludge pyrolysis was calculated by a non-isothermal kinetic. Arrhenius activation energy was lower for the pyrolysis of a digested grease sample (92 kJ mol−1 obtained by OFW and 86 kJ mol−1 obtained by Vyazovkin) than for the pyrolysis of sewage sludge and its blends (164–190 kJ mol−1 obtained by OFW and 162–190 kJ mol−1 obtained by Vyazovkin). The analysis of the integrated approach of anaerobic co-digestion and pyrolysis of digestates demonstrated that the addition of 3% (w/v) of fat to the feeding sludge results in a 25% increase in the electricity obtained from biogas (if a combined heat and power unit is considered for biogas valorisation) and increasing the fat content to 15% allows for covering all thermal needs for drying of digestate and more than doubles (2.4 times) the electricity production when the scenario of digestion and pyrolysis is contemplated.S

Simulations of anomalous ion diffusion in experimentally measured turbulent potential

The diffusion of plasma impurities in tokamak-edge-plasma turbulence is investigated numerically. The time-dependent potential governing particle motion was measured by 2D array of 8×8 Langmuir probes in edge region of CASTOR tokamak. The diffusion of particles is found to be classical in the radial direction, but it can be of an anomalous Lévy-walk type in the poloidal direction. The diffusion is found to be dependent on the ratio of particles' mass and charge. When this ratio grows, the diffusion coefficient in radial direction grows as well, whereas poloidal diffusion coefficient drops down. Moreover, movement of particles in the time-frozen snapshot of this potential is investigated showing that also the time-independent potential is much more favorable for the particle diffusion in poloidal direction than in radial one. In the case of single ionized carbon ions the poloidal diffusion in time-independent potential transits to the Lévy-walk type for temperatures greater than 25 eV, for radial diffusion Lévy-walk was not observed even for 500 eV

The optimization of resonant magnetic perturbation spectra for the COMPASS tokamak

The COMPASS tokamak, recently transferred from UKAEA Culham to IPP Prague, is equipped with a set of saddle coils for producing controlled resonant magnetic perturbations (RMPs). In the future experimental programme of COMPASS we plan to focus on studies of RMPs, especially in view of their application as an ELM control mechanism and their considered use in ITER. In the present contribution we describe the preparatory calculations for the planned experiments. We computed the spectra of perturbations for several different equilibria predicted by MHD simulations and determined the positions and sizes of the resulting islands. It is shown how the saddle coils of COMPASS can be adapted to our equilibria to obtain good island overlap at the edge, which is believed to be a key component in the ELM mitigation effect. The techniques used for adapting the coils to achieve this result are described. Those are fairly general and could be used in the design of RMP coils on other machines