Oregon Wine Board Meeting Minutes September 11, 2012

These meeting minutes list individuals in attendance and missing at the September 11, 2012 Oregon Wine Board (OWB) meeting, held via conference call. Dewey Weddington provided a marketing update focused on planning for Oregon Wine Month and the Oregon Wine Industry Symposium. The meeting also included discussion of the 2011-2012 year-end financial review and a presentation of the budget for the following year. The meeting lasted 2 hours 6 minutes, and the Board went into Executive Session after the meeting was adjourned

Радиационно-химический синтез перфторированной полимерной мембраны с сульфокислотными группами

В результаті радіаційно-індукованої прищепної сополімеризації з водних розчинів двох мономерів — акрилової кислоти і натрієвої солі стиролсульфонату — на полімерну плівку з фторованого пропілену-етилену синтезована протонобмінна мембрана з сульфокислотними групами. Розглянуті основні експериментальні параметри, що впливають на процес прищепної сополімеризації.Sulfonic acid proton exchange membranes based on a poly(tetrafluoroethylene-co-hexafluoropropylene) film are synthesized through the graft copolymerization of sodium styrenesulfonate and acrylic acid monomers from binary monomer aqueous solutions. The effects of the main polymerization parameters on the degree of grafting are studied

Impact of phosphate dosing on the microbial ecology of drinking water distribution systems: fieldwork studies in chlorinated networks

Phosphate is routinely dosed to ensure regulatory compliance for lead in drinking water distribution systems. Little is known about the impact of the phosphate dose on the microbial ecology in these systems and in particular the endemic biofilms. Disturbance of the biofilms and embedded material in distribution can cause regulatory failures for turbidity and metals. To investigate the impact of phosphate on developing biofilms, pipe wall material from four independent pipe sections was mobilised and collected using two twin-flushing operations a year apart in a chlorinated UK network pre- and post-phosphate dosing. Intensive monitoring was undertaken, including turbidity and water physico-chemistry, traditional microbial culture-based indicators, and microbial community structure via sequencing the 16S rRNA gene for bacteria and the ITS2 gene for fungi. Whole metagenome sequencing was used to study shifts in functional characteristics following the addition of phosphate. As an operational consequence, turbidity responses from the phosphate-enriched water were increased, particularly from cast iron pipes. Differences in the taxonomic composition of both bacteria and fungi were also observed, emphasising a community shift towards microorganisms able to use or metabolise phosphate. Phosphate increased the relative abundance of bacteria such as Pseudomonas, Paenibacillus, Massilia, Acinetobacter and the fungi Cadophora, Rhizophagus and Eupenicillium. Whole metagenome sequencing showed with phosphate a favouring of sequences related to Gram-negative bacterium type cell wall function, virions and thylakoids, but a reduction in the number of sequences associated to vitamin binding, methanogenesis and toxin biosynthesis. With current faecal indicator tests only providing risk detection in bulk water samples, this work improves understanding of how network changes effect microbial ecology and highlights the potential for new approaches to inform future monitoring or control strategies to protect drinking water quality

OGRE: Overlap Graph-based metagenomic Read clustEring

The microbes that live in an environment can be identified from the genomic material that is present, also referred to as the metagenome. Using Next Generation Sequencing techniques this genomic material can be obtained from the environment, resulting in a large set of sequencing reads. A proper assembly of these reads into contigs or even full genomes allows one to identify the microbial species and strains that live in the environment. Assembling a metagenome is a challenging task and can benefit from clustering the reads into species-specific bins prior to assembly. In this paper we propose OGRE, an Overlap-Graph based Read clustEring procedure for metagenomic read data. OGRE is the only method that can successfully cluster reads in species-specific bins for large metagenomic datasets without running into computation time- or memory issues

Microbial diversity, ecological networks and functional traits associated to materials used in drinking water distribution systems

Drinking water distribution systems host complex microbial communities as biofilms that interact continuously with delivered water. Understanding the diversity, behavioural and functional characteristics will be a requisite for developing future monitoring strategies and protection against water-borne health risks. To improve understanding, this study investigates mobilisation and accumulation behaviour, microbial community structure and functional variations of biofilms developing on different pipe materials from within an operational network. Samples were collected from four pipes during a repeated flushing operation three months after an initial visit that used hydraulic forces to mobilise regenerating biofilms yet without impacting the upstream network. To minimise confounding factors, test sections were chosen with comparable daily hydraulic regimes, physical dimensions, and all connected straight of a common trunk main and within close proximity, hence similar water chemistry, pressure and age. Taxonomical results showed differences in colonising communities between pipe materials, with several genera, including the bacteria Pseudomonas and the fungi Cladosporium, present in every sample. Diverse bacterial communities dominated compared to more homogeneous fungal, or mycobiome, community distribution. The analysis of bacterial/fungal networks based on relative abundance of operational taxonomic units (OTUs) indicated microbial communities from cast iron pipes were more stable than communities from the non-ferrous pipe materials. Novel analysis of functional traits between all samples were found to be mainly associated to mobile genetic elements that play roles in determining links between cells, including phages, prophages, transposable elements, and plasmids. The use of functional traits can be considered for development in future surveillance methods, capable of delivering network condition information beyond that of limited conventional faecal indicator tests, that will help protect water quality and public health

Cell wall changes during maturation of conidia in Pseudallescheria boydii

International audienc

Identical sequences found in distant genomes reveal frequent horizontal transfer across the bacterial domain

Horizontal Gene Transfer (HGT) is an essential force in microbial evolution. Despite detailed studies on a variety of systems, a global picture of HGT in the microbial world is still missing. Here, we exploit that HGT creates long identical DNA sequences in the genomes of distant species, which can be found efficiently using alignment-free methods. Our pairwise analysis of 93 481 bacterial genomes identified 138 273 HGT events. We developed a model to explain their statistical properties as well as estimate the transfer rate between pairs of taxa. This reveals that long-distance HGT is frequent: our results indicate that HGT between species from different phyla has occurred in at least 8% of the species. Finally, our results confirm that the function of sequences strongly impacts their transfer rate, which varies by more than 3 orders of magnitude between different functional categories. Overall, we provide a comprehensive view of HGT, illuminating a fundamental process driving bacterial evolution

Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease caused by aberrations in the genome. While several disea

Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype

Motivation: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease caused by aberrations in the genome. While several disease-causing variants have been identified, a major part of heritability remains unexplained. ALS is believed to have a complex genetic basis where non-additive combinations of variants constitute disease, which cannot be picked up using the linear models employed in classical genotype-phenotype association studies. Deep learning on the other hand is highly promising for identifying such complex relations. We therefore developed a deep-learning based approach for the classification of ALS patients versus healthy individuals from the Dutch cohort of the Project MinE dataset. Based on recent insight that regulatory regions harbor the majority of disease-associated variants, we employ a two-step approach: first promoter regions that are likely associated to ALS are identified, and second individuals are classified based on their genotype in the selected genomic regions. Both steps employ a deep convolutional neural network. The network architecture accounts for the structure of genome data by applying convolution only to parts of the data where this makes sense from a genomics perspective. Results: Our approach identifies potentially ALS-associated promoter regions, and generally outperforms other classification methods. Test results support the hypothesis that non-additive combinations of variants contribute to ALS. Architectures and protocols developed are tailored toward processing population-scale, whole-genome data. We consider this a relevant first step toward deep learning assisted genotype-phenotype association in whole genome-sized data