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Arsenic (As) contamination of drinking water is a global issue, affecting health of millions of people in many countries. Drinking water companies in the Netherlands have recently established 1 µg/L as the guideline for As in drinking water based on dose-effect modelling of low-level As in Dutch drinking water which has shown that 10 µg/L is not sufficiently protective for the health of Dutch population. In the Netherlands some of the water treatment plants (WTPs) produce drinking water with higher than 1 µg/L As and currently Dutch drinking water companies are investigating options to reduce As to <1 µg/L at these WTPs.

Het doel van dit onderzoek is om binnen Kragten de expertise op het gebied van de droogte-aanpak te vergroten. Onderdeel hiervan is het opstellen van een maatregelenpakket om droogte- effecten in de beeksystemen van de Snelle Loop en Bakelse Aa te voorkomen en/of te mitigeren. Het resultaat is een maatregelenpakket voor de twee beeksystemen welke als input kunnen dienen voor concrete herinrichtingsprojecten. De onderzoeksvraag is: Welke maatregelen dragen bij aan het voorkomen en/of mitigeren van de effecten van droogte in de beeksystemen van de Snelle Loop en de Bakelse Aa?

The 2003 redoubling in power to 68MW on the Polokwane Smelter furnace represented a significant intensification in platinum group metal (PGM) smelting. Combined with onerous 'green' PGM concentrate smelting requirements, this yielded conditions unusually corrosive to copper coolers and refractories. This presented unexpected operational and design challenges to reliable crucible operation and maintenance. Combined with specific operational control intervention, development of protective coatings has led to the life of water-cooled copper components improving from 9 to 40 months. The furnace matte endwall was extended in 2010 to address accelerated wear of refractories and the potential risk for contact of copper components by superheated matte. An 18 month planned endwall rebuild cycle has been demonstrated (versus catastrophic failure within 9 months). Finally, benefits including lower energy consumption, improved metal recoveries and higher productivity resulting from operational and in-house design developments will be described, that justify "Celebrating the Mega-scale" in PGM smelting.

The value of the multivariate data analysis tools principal component analysis (PCA) and principal component discriminant analysis (PCDA) for prioritizing leads generated by microarrays was evaluated. To this end, Pseudomonas putida S12 was grown in independent triplicate fermentations on four different carbon sources, i.e. fructose, glucose, gluconate and succinate. RNA isolated from these samples was analysed in duplicate on an anonymous clone-based array to avoid bias during data analysis. The relevant transcripts were identified by analysing the loadings of the principal components (PC) and discriminants (D) in PCA and PCDA, respectively. Even more specifically, the relevant transcripts for a specific phenotype could also be ranked from the loadings under an angle (biplot) obtained after PCDA analysis. The leads identified in this way were compared with those identified using the commonly applied fold-difference and hierarchical clustering approaches. The different data analysis methods gave different results. The methods used were complementary and together resulted in a comprehensive picture of the processes important for the different carbon sources studied. For the more subtle, regulatory processes in a cell, the PCDA approach seemed to be the most effective. Except for glucose and gluconate dehydrogenase, all genes involved in the degradation of glucose, gluconate and fructose were identified. Moreover, the transcriptomics approach resulted in potential new insights into the physiology of the degradation of these carbon sources. Indications of iron limitation were observed with cells grown on glucose, gluconate or succinate but not with fructose-grown cells. Moreover, several cytochrome- or quinone-associated genes seemed to be specifically up- or downregulated, indicating that the composition of the electron-transport chain in P. putida S12 might change significantly in fructose-grown cells compared to glucose-, gluconate- or succinate-grown cells. © 2006

Messenger RNA levels change on a minutes scale due to both degradation and de novo transcription. Consequently, alterations in the transcript profiles that are not representative for the condition of interest are easily introduced during sample harvesting and work-up. In order to avoid these unwanted changes we have validated a - 45°C methanol-based quenching method for obtaining reliable and reproducible 'snapshot' samples of Lactobacillus plantarum cells for transcriptome analyses. Transcript profiles of cells harvested with the quenching method were compared with transcript profiles of cells that were harvested according to two different commonly applied protocols. Significant differences between the transcript profiles of cells harvested by the different methods from the same steady-state culture were observed. In total, 42 genes or operons were identified from which the transcript levels were altered when the cells were not immediately quenched upon harvesting. Among these, several have previously been associated with cold-shock response. Furthermore, the reproducibility of transcript profiles improved, as indicated by the fact that the variation in the data sets obtained from the quenched cells was smaller than in the data sets obtained from the cells that were harvested under non-quenched conditions. © 2005 Elsevier B.V. All rights reserved.

Many cellular processes are regulated at the transcriptional level. For this reason the transcriptome of a cell, the total set of RNAs under a specific condition, contains information about the biological state of the cell and the genes that play a role under specific circumstances.Transcriptomics is the research method that studies the effect of specific conditions on alterations in the expression levels of complete sets of genes. This thesis describes the application and optimization of transcriptomics and transcriptomics-related techniques in studies on lactic acid and sodium chloride stress-related gene expression in Lactobacillus plantarum WCFS1. The complete genomic sequence of this strain is available, and the organism is used as a model strain for lactic acid bacteria in industrial applications and host-microbe interactions.In order to maximize specificity and reliability of transcriptome data, a quenching protocol for the isolation of microbial cells from submerged cultures was implemented and validated. The results from this study revealed a significant positive effect of the quenching protocol on the conservation of the transcriptome, and consequently on the reliability and representativity of the gene expression data.Transcriptome analyses were performed with clone-based microarrays. In order to optimise the potential of clone-based arrays for transcriptomics studies of strains from which the complete genomic sequence is not available, two complementary equations were developed that allow for mathematical design of such an array.The first equation predicts the fraction of genes that is represented on the array in a detectable way and cover at least a set part of the genomic fragment on the array. The second equation predicts the fraction of genes for which information can be interpreted in a quantitative way.The effect of lactic acid on gene expression in L. plantarum was studied by means of an experimental design that allows for the distinction between

Background: Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a random process, it is beforehand uncertain which genes are represented. Nevertheless, the genome coverage of such an array, which depends on different variables like the insert size and the number of clones in the library, can be predicted by mathematical approaches. When applying the classical formulas that determine the probability that a certain sequence is represented in a DNA library at the nucleotide level, massive amounts of clones would be necessary to obtain a proper coverage of the genome. Results: This paper describes the development of two complementary equations for determining the genome coverage at the gene level. The first equation predicts the fraction of genes that is represented on the array in a detectable way and cover at least a set part (the minimal insert coverage) of the genomic fragment by which these enes are represented. The higher this minimal insert coverage, the larger the chance that changes in expression of a specific gene can be detected and attributed to that gene. The second equation predicts the fraction of genes that is represented in spots on the array that only represent genes from a single transcription unit, which information can be interpreted in a quantitative way. Conclusion: Validation of these equations shows that they form reliable tools supporting optimal design of prokaryotic clone-based microarrays. © 2005 Pieterse et al; licensee BioMed Central Ltd.

Background - Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a random process, it is beforehand uncertain which genes are represented. Nevertheless, the genome coverage of such an array, which depends on different variables like the insert size and the number of clones in the library, can be predicted by mathematical approaches. When applying the classical formulas that determine the probability that a certain sequence is represented in a DNA library at the nucleotide level, massive amounts of clones would be necessary to obtain a proper coverage of the genome. Results - This paper describes the development of two complementary equations for determining the genome coverage at the gene level. The first equation predicts the fraction of genes that is represented on the array in a detectable way and cover at least a set part (the minimal insert coverage) of the genomic fragment by which these genes are represented. The higher this minimal insert coverage, the larger the chance that changes in expression of a specific gene can be detected and attributed to that gene. The second equation predicts the fraction of genes that is represented in spots on the array that only represent genes from a single transcription unit, which information can be interpreted in a quantitative way. Conclusion - Validation of these equations shows that they form reliable tools supporting optimal design of prokaryotic clone-based microarrays.