Cinétiques de biodégradation par boues activées de la matière organique soluble d'un effluent synthétique

L'approche expérimentale choisie pour cette étude a eu pour objet de mesurer en conditions batch, les cinétiques d'élimination de la demande chimique en oxygène soluble d'un effluent synthétique mis en contact avec des boues activées d'origine différente. Les essais conduits en laboratoire ont été réalisés en faisant varier le rapport So/Xo (mg de DCO initiale par mg de matières volatiles initiales) telles que les concentrations en So et en Xo correspondent aux concentrations en DCO soluble (DCOs) et en matières volatiles (MV) rencontrées sur les stations d'épuration. Les essais ont été effectués sous aération continue à 20 °C en mettant en contact l'effluent synthétique et de la boue activée prélevée depuis 24 h et stockée à 4 °C dans l'attente de l'essai. De ce fait, la valeur de So mesurée au début de l'essai représente la concentration en DCO amenée par l'effluent synthétique (Seff) et celle amenée par l'inoculum de boue activée (Sb) représentant selon les essais de 5 à 70 % de la DCO de l'essai. Les profils de cinétique d'élimination de la DCO soluble obtenus pour différentes conditions d'essai s'ajustent, selon les valeurs de So/Xo (So/Xo variant de 0,15 à 2,17 ) à une fonction du premier ordre par rapport au substrat ou à une fonction sigmoïde. Le type de fonction cinétique d'élimination est également contrôlé par la proportion de la DCO amenée par l'inoculum.The conventional activated sludge process used for wastewater treatment removes from 80 to 95% of the total organic matter. However, a quantity of "not well identified" (particular, colloidal and soluble) organic matter is always present in the treated effluent. Reducing this residual (and improving the treatment efficiency) requires knowledge of the origin of that organic matter and especially to determine the fraction originating from the influent and the fraction generated by the biomass.This research has been conducted in batch conditions and studies the soluble COD (CODs) removal kinetics of a synthetic effluent (casein + starch + acetate + mineral salts), in contact with different activated sludge originating from six different wastewater treatment plants (loads varying from 0.06 to 1.14 kg BOD[inf]5/kg VSS. d).Experiments have been conducted with different So/Xo values (ratio between CODs initial concentration and VSS initial concentration) in order that these values correspond to the CODs and VSS values found in the plants.In accordance with GRAU et al. (1975), CECH and CHUDOBA (1983), PITTER and CHUDOBA (1990), CHUDOBA et al (1992), the So/Xo ratio is a fundamental parameter governing the kinetics reactions.Experiments have been conducted under continuous aeration at 20°C where the synthetic wastewater (500 ml) is in contact with activated sludge (200 ml) collected 24 h before and stored at 4°C until the batch is started. In this manner, the initial So is due to the CODs of the synthetic effluent (So eff=197 mg/l) and to the CODs originating from the sludge (5 to 70% of the initial CODs). The initial VSS concentration (Xo) is between 0.6 and 2.5 g/l. Kinetics of CODs removal are simulated by two functions: the first order function, where the initial rate is the maximal, and the sigmoidal function where the maximal rate is reached after a lag time (3 to 8 h).Concerning the first order functions, the degradation rate is faster when the ratio is low (So/Xo lower than 0.44). This is not the case for the sigmoidal functions. In the results of this study, the residual of COD is always lower when the degradation kinetic follows the exponential model.Our experiments show that the type of degradation kinetics (first order or sigmoidal) is not only controlled by the So/Xo parameter but also by the proportion of CODs brought by the sludge and that parameter can play a determinant role.When the proportion of CODs brought by the sludge is very large (between 41% to 46%) the degradation reactions follow the sigmoidal type. These results can possibly be explained by the low biodegradability of the polymers or molecules originating from the inoculum which has been stored during 24 h, or by the low activity of the biomass after 24 h of storage on the biodegradation of the soluble organic matte

Simcluster: clustering enumeration gene expression data on the simplex space

Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space.

Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster.

Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data

Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework

<p>Abstract</p> <p>Background</p> <p>Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Standard analyses of SAGE data, however, ignore the fact that the probability of generating an observable tag varies across genes and between experiments. As a consequence, these analyses result in biased estimators and posterior probability intervals for gene expression levels in the transcriptome.</p> <p>Results</p> <p>Using the yeast <it>Saccharomyces cerevisiae </it>as an example, we introduce a new Bayesian method of data analysis which is based on a model of SAGE tag formation. Our approach incorporates the variation in the probability of tag formation into the interpretation of SAGE data and allows us to derive exact joint and approximate marginal posterior distributions for the mRNA frequency of genes detectable using SAGE. Our analysis of these distributions indicates that the frequency of a gene in the tag pool is influenced by its mRNA frequency, the cleavage efficiency of the anchoring enzyme (AE), and the number of informative and uninformative AE cleavage sites within its mRNA.</p> <p>Conclusion</p> <p>With a mechanistic, model based approach for SAGE data analysis, we find that inter-genic variation in SAGE tag formation is large. However, this variation can be estimated and, importantly, accounted for using the methods we develop here. As a result, SAGE based estimates of mRNA frequencies can be adjusted to remove the bias introduced by the SAGE tag formation process.</p

The Genome of Borrelia recurrentis, the Agent of Deadly Louse-Borne Relapsing Fever, Is a Degraded Subset of Tick-Borne Borrelia duttonii

In an effort to understand how a tick-borne pathogen adapts to the body louse, we sequenced and compared the genomes of the recurrent fever agents Borrelia recurrentis and B. duttonii. The 1,242,163–1,574,910-bp fragmented genomes of B. recurrentis and B. duttonii contain a unique 23-kb linear plasmid. This linear plasmid exhibits a large polyT track within the promoter region of an intact variable large protein gene and a telomere resolvase that is unique to Borrelia. The genome content is characterized by several repeat families, including antigenic lipoproteins. B. recurrentis exhibited a 20.4% genome size reduction and appeared to be a strain of B. duttonii, with a decaying genome, possibly due to the accumulation of genomic errors induced by the loss of recA and mutS. Accompanying this were increases in the number of impaired genes and a reduction in coding capacity, including surface-exposed lipoproteins and putative virulence factors. Analysis of the reconstructed ancestral sequence compared to B. duttonii and B. recurrentis was consistent with the accelerated evolution observed in B. recurrentis. Vector specialization of louse-borne pathogens responsible for major epidemics was associated with rapid genome reduction. The correlation between gene loss and increased virulence of B. recurrentis parallels that of Rickettsia prowazekii, with both species being genomic subsets of less-virulent strains

PatternLab for proteomics: a tool for differential shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu <it>et al</it>. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen <it>et al</it>. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.</p> <p>Results</p> <p>To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen <it>et al</it>. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine) because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies.</p> <p>Conclusion</p> <p>PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche. Additionally, graphing tools are available to aid in the analysis of high throughput experimental data. PatternLab is available at <url>http://pcarvalho.com/patternlab</url>.</p

Clustering-based approaches to SAGE data mining

Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation

Tau-Mediated Nuclear Depletion and Cytoplasmic Accumulation of SFPQ in Alzheimer's and Pick's Disease

Tau dysfunction characterizes neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Here, we performed an unbiased SAGE (serial analysis of gene expression) of differentially expressed mRNAs in the amygdala of transgenic pR5 mice that express human tau carrying the P301L mutation previously identified in familial cases of FTLD. SAGE identified 29 deregulated transcripts including Sfpq that encodes a nuclear factor implicated in the splicing and regulation of gene expression. To assess the relevance for human disease we analyzed brains from AD, Pick's disease (PiD, a form of FTLD), and control cases. Strikingly, in AD and PiD, both dementias with a tau pathology, affected brain areas showed a virtually complete nuclear depletion of SFPQ in both neurons and astrocytes, along with cytoplasmic accumulation. Accordingly, neurons harboring either AD tangles or Pick bodies were also depleted of SFPQ. Immunoblot analysis of human entorhinal cortex samples revealed reduced SFPQ levels with advanced Braak stages suggesting that the SFPQ pathology may progress together with the tau pathology in AD. To determine a causal role for tau, we stably expressed both wild-type and P301L human tau in human SH-SY5Y neuroblastoma cells, an established cell culture model of tau pathology. The cells were differentiated by two independent methods, mitomycin C-mediated cell cycle arrest or neuronal differentiation with retinoic acid. Confocal microscopy revealed that SFPQ was confined to nuclei in non-transfected wild-type cells, whereas in wild-type and P301L tau over-expressing cells, irrespective of the differentiation method, it formed aggregates in the cytoplasm, suggesting that pathogenic tau drives SFPQ pathology in post-mitotic cells. Our findings add SFPQ to a growing list of transcription factors with an altered nucleo-cytoplasmic distribution under neurodegenerative conditions