Antibiotic resistant bacteria/genes dissemination in lacustrine sediments highly increased following cultural eutrophication of Lake Geneva (Switzerland).

This study investigates faecal indicator bacteria (FIB), multiple antibiotic resistant (MAR), and antibiotic resistance genes (ARGs), of sediment profiles from different parts of Lake Geneva (Switzerland) over the last decades. MARs consist to expose culturable Escherichia coli (EC) and Enterococcus (ENT) to mixed five antibiotics including Ampicillin, Tetracycline, Amoxicillin, Chloramphenicol and Erythromycin. Culture-independent is performed to assess the distribution of ARGs responsible for, β-lactams (blaTEM; Amoxicillin/Ampicillin), Streptomycin/Spectinomycin (aadA), Tetracycline (tet) Chloramphenicol (cmlA) and Vancomycin (van). Bacterial cultures reveal that in the sediments deposited following eutrophication of Lake Geneva in the 1970s, the percentage of MARs to five antibiotics varied from 0.12% to 4.6% and 0.016% to 11.6% of total culturable EC and ENT, respectively. In these organic-rich bacteria-contaminated sediments, the blaTEM resistant of FIB varied from 22% to 48% and 16% to 37% for EC and ENT respectively, whereas the positive PCR assays responsible for tested ARGs were observed for EC, ENT, and total DNA from all samples. The aadA resistance gene was amplified for all the sediment samples, including those not influenced by WWTP effluent water. Our results demonstrate that bacteria MARs and ARGs highly increased in the sediments contaminated with WWTP effluent following the cultural eutrophication of Lake Geneva. Hence, the human-induced changing limnological conditions highly enhanced the sediment microbial activity, and therein the spreading of antibiotic resistant bacteria and genes in this aquatic environment used to supply drinking water in a highly populated area. Furthermore, the presence of the antibiotic resistance gene aadA in all the studied samples points out a regional dissemination of this emerging contaminant in freshwater sediments since at least the late nineteenth century.

Sulfur and strontium isotope composition of the Llobregat River (NE Spain): Tracers of natural and anthropogenic chemicals in stream waters

The use of sulfur and strontium isotopes as tracers for the source/s of water contaminants have been applied to the water of the Llobregat River system (NE Spain). Surface water samples from June 1997 were collected from the Llobregat River and its main tributaries and creeks. The chemistry of most stream waters are controlled mainly by the weathering of Tertiary chemical sediments within the drainage basin. The largest variation in delta(34)S values were found in the small creeks with values ranging from -9.9 to 15parts per thousand, whilst in the main river channels values ranged from 6.3 to 12.4parts per thousand. The Sr-87/Sr-86 ratio for dissolved strontium ranged from 0.70795 for a non-polluted site to 0.70882 for a polluted one. Most of the waters with high NO3 and low Ca/Na ratio converge to the same Sr-87/Sr-86 value, pointing to dominant pollutant end member contribution or a mixing of pollutants with an isotopic composition around 0.7083-0.7085. Although the concentration of the natural inputs in the river for sulfate and strontium are high, as a result of the sulfate outcrops within the geology of the basin, their isotopic characteristics suggest that they can be used as a discriminating device in water pollution problems. However to establish the detailed characteristics of the isotopes as geochemical tools, specific high-resolution case studies are necessary in small areas, where the inputs are well known.

Heated Optical Fiber for Distributed Soil-Moisture Measurements: A Lysimeter Experiment

An Actively Heated Fiber Optics (AHFO) method to estimate soil moisture is tested and the analysis technique improved on. The measurements were performed in a lysimeter uniformly packed with loam soil with variable water content profiles. In the first meter of the soil profi le, 30 m of fiber optic cable were installed in a 12 loops coil. The metal sheath armoring the fiber cable was used as an electrical resistance heater to generate a heat pulse, and the soil response was monitored with a Distributed Temperature Sensing (DTS) system. We study the cooling following three continuous heat pulses of 120 s at 36 W m(-1) by means of long-time approximation of radial heat conduction. The soil volumetric water contents were then inferred from the estimated thermal conductivities through a specifically calibrated model relating thermal conductivity and volumetric water content. To use the pre-asymptotic data we employed a time correction that allowed the volumetric water content to be estimated with a precision of 0.01-0.035 (m(3) m(-3)). A comparison of the AHFO measurements with soil-moisture measurements obtained with calibrated capacitance-based probes gave good agreement for wetter soils [discrepancy between the two methods was less than 0.04 (m(3) m(-3))]. In the shallow drier soils, the AHFO method underestimated the volumetric water content due to the longertime required for the temperature increment to become asymptotic in less thermally conductive media [discrepancy between the two methods was larger than 0.1 (m(3) m(-3))]. The present work suggests that future applications of the AHFO method should include longer heat pulses, that longer heating and cooling events are analyzed, and, temperature increments ideally be measured with higher frequency.

Fate of the herbicide glyphosate and its metabolite AMPA in soils and their transfer to surface waters: A multi-scale approach in the Lavaux vineyards, western Switzerland

The use of herbicides in agriculture may lead to environmental problems, such as surface water pollution, with a potential risk for aquatic organisms. The herbicide glyphosate is the most used active ingredient in the world and in Switzerland. In the Lavaux vineyards it is nearly the only molecule applied. This work aimed at studying its fate in soils and its transfer to surface waters, using a multi-scale approach: from molecular (10-9 m) and microscopic scales (10-6 m), to macroscopic (m) and landscape ones (103 m). First of all, an analytical method was developed for the trace level quantification of this widely used herbicide and its main by-product, aminomethylphosphonic acid (AMPA). Due to their polar nature, their derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl) was done prior to their concentration and purification by solid phase extraction. They were then analyzed by ultra performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). The method was tested in different aqueous matrices with spiking tests and validated for the matrix effect correction in relevant environmental samples. Calibration curves established between 10 and 1000ng/l showed r2 values above 0.989, mean recoveries varied between 86 and 133% and limits of detection and quantification of the method were as low as 5 and 10ng/l respectively. At the parcel scale, two parcels of the Lavaux vineyard area, located near the Lutrive River at 6km to the east of Lausanne, were monitored to assess to which extent glyphosate and AMPA were retained in the soil or exported to surface waters. They were equipped at their bottom with porous ceramic cups and runoff collectors, which allowed retrieving water samples for the growing seasons 2010 and 2011. Results revealed that the mobility of glyphosate and AMPA in the unsaturated zone was likely driven by the precipitation regime and the soil characteristics, such as slope, porosity structure and layer permeability discrepancy. Elevated glyphosate and AMPA concentrations were measured at 60 and 80 cm depth at parcel bottoms, suggesting their infiltration in the upper parts of the parcels and the presence of preferential flow in the studied parcels. Indeed, the succession of rainy days induced the gradual saturation of the soil porosity, leading to rapid infiltration through macropores, as well as surface runoff formation. Furthermore, the presence of more impervious weathered marls at 100 cm depth induced throughflows, the importance of which for the lateral transport of the herbicide molecules was determined by the slope steepness. Important rainfall events (>10 mm/day) were clearly exporting molecules from the soil top layer, as indicated by important concentrations in runoff samples. A mass balance showed that total loss (10-20%) mainly occurred through surface runoff (96%) and, to a minor extent, by throughflows in soils (4%), with subsequent exfiltration to surface waters. Observations made in the Lutrive River revealed interesting details of glyphosate and AMPA dynamics in urbanized landscapes, such as the Lavaux vineyards. Indeed, besides their physical and chemical properties, herbicide dynamics at the catchment level strongly depend on application rates, precipitation regime, land use and also on the presence of drains or constructed channels. Elevated concentrations, up to 4970 ng/l, observed just after the application, confirmed the diffuse export of these compounds from the vineyard area by surface runoff during main rain events. From April to September 2011, a total load of 7.1 kg was calculated, with 85% coming from vineyards and minor urban sources and 15% from arable crops. Small vineyard surfaces could generate high concentrations of herbicides and contribute considerably to the total load calculated at the outlet, due to their steep slopes (~10%). The extrapolated total amount transferred yearly from the Lavaux vineyards to the Lake of Geneva was of 190kg. At the molecular scale, the possible involvement of dissolved organic matter (DOM) in glyphosate and copper transport was studied using UV/Vis fluorescence spectroscopy. Combined with parallel factor (PARAFAC) analysis, this technique allowed characterizing DOM of soil and surface water samples from the studied vineyard area. Glyphosate concentrations were linked to the fulvic-like spectroscopic signature of DOM in soil water samples, as well as to copper, suggesting the formation of ternary complexes. In surface water samples, its concentrations were also correlated to copper ones, but not in a significant way to the fulvic-like signature. Quenching experiments with standards confirmed field tendencies in the laboratory, with a stronger decrease in fluorescence intensity for fulvic-like fluorophore than for more aromatic ones. Lastly, based on maximum concentrations measured in the river, an environmental risk for these compounds was assessed, using laboratory tests and ecotoxicity data from the literature. In our case and with the methodology applied, the risk towards aquatic species was found negligible (RF<1).

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Improved detection of Rhodococcus coprophilus with a new quantitative PCR assay.

Agricultural practices, such as spreading liquid manure or the utilisation of land as animal pastures, can result in faecal contamination of water resources. Rhodococcus coprophilus is used in microbial source tracking to indicate animal faecal contamination in water. Methods previously described for detecting of R. coprophilus in water were neither sensitive nor specific. Therefore, the aim of this study was to design and validate a new quantitative polymerase chain reaction (qPCR) to improve the detection of R. coprophilus in water. The new PCR assay was based on the R. coprophilus 16S rRNA gene. The validation showed that the new approach was specific and sensitive for deoxyribunucleic acid from target host species. Compared with other PCR assays tested in this study, the detection limit of the new qPCR was between 1 and 3 log lower. The method, including a filtration step, was further validated and successfully used in a field investigation in Switzerland. Our work demonstrated that the new detection method is sensitive and robust to detect R. coprophilus in surface and spring water. Compared with PCR assays that are available in the literature or to the culture-dependent method, the new molecular approach improves the detection of R. coprophilus.

Measurement of absolute cell volume, osmotic membrane water permeability, and refractive index of transmembrane water and solute flux by digital holographic microscopy.

ABSTRACT. A dual-wavelength digital holographic microscope to measure absolute volume of living cells is proposed. The optical setup allows us to reconstruct two quantitative phase contrast images at two different wavelengths from a single hologram acquisition. When adding the absorbing dye fast green FCF as a dispersive agent to the extracellular medium, cellular thickness can be univocally determined in the full field of view. In addition to the absolute cell volume, the method can be applied to derive important biophysical parameters of living cells including osmotic membrane water permeability coefficient and the integral intracellular refractive index (RI). Further, the RI of transmembrane flux can be determined giving an indication about the nature of transported solutes. The proposed method is applied to cultured human embryonic kidney cells, Chinese hamster ovary cells, human red blood cells, mouse cortical astrocytes, and neurons.

Pollution and pollutant transport in the geosphere - An introduction to the symposium

Environmental research in earth sciences is focused on the geosphere, i.e. (1) waters and sediments of rivers, lakes and oceans, and (2) soils and underlying shallow rock formations,both water-unsaturated and -saturated. The subsurface is studied down to greater depths at sites where waste repositories or tunnels are planned and mining activities exist. In recent years, earth scientists have become more and more involved in pollution problems related to their classical field of interest, e.g. groundwater, ore deposits, or petroleum and non-metal natural deposits (gravel, clay, cement precursors). Major pollutants include chemical substances, radioactive isotopes and microorganisms. Mechanisms which govern the transport of pollutants are of physical, chemical (dissolution, precipitation, adsorption), or microbiological (transformation) nature. Land-use planning must reflect a sustainable development and sound scientific criteria. Today's environmental pollution requires working teams with an interdisciplinary background in earth sciences, hydrology, chemistry, biology, physics as well as engineering. This symposium brought together for the first time in Switzerland earth and soil scientists, physicists and chemists, to present and discuss environmental issues concerning the geosphere.

Energy expenditure by doubly labeled water: validation in humans and proposed calculation.

To further validate the doubly labeled water method for measurement of CO2 production and energy expenditure in humans, we compared it with near-continuous respiratory gas exchange in nine healthy young adult males. Subjects were housed in a respiratory chamber for 4 days. Each received 2H2(18)O at either a low (n = 6) or a moderate (n = 3) isotope dose. Low and moderate doses produced initial 2H enrichments of 5 and 10 X 10(-3) atom percent excess, respectively, and initial 18O enrichments of 2 and 2.5 X 10(-2) atom percent excess, respectively. Total body water was calculated from isotope dilution in saliva collected at 4 and 5 h after the dose. CO2 production was calculated by the two-point method using the isotopic enrichments of urines collected just before each subject entered and left the chamber. Isotope enrichments relative to predose samples were measured by isotope ratio mass spectrometry. At low isotope dose, doubly labeled water overestimated average daily energy expenditure by 8 +/- 9% (SD) (range -7 to 22%). At moderate dose the difference was reduced to +4 +/- 5% (range 0-9%). The isotope elimination curves for 2H and 18O from serial urines collected from one of the subjects showed expected diurnal variations but were otherwise quite smooth. The overestimate may be due to approximations in the corrections for isotope fractionation and isotope dilution. An alternative approach to the corrections is presented that reduces the overestimate to 1%.

The Use of Passive Samplers to Reveal Industrial and Agricultural Pollution Trends in Swiss Rivers

This study shows the efficiency of passive sampling to reveal industrial and agricultural pollution trends. Two practical applications for nonpolar and polar contaminants are presented. Low-density polyethylene (LDPE) samplers were deployed for one year in the Venoge River (VD) to monitor indicator PCBs (iPCBs, IUPAC nos. 28, 52, 101, 138, 153 and 180). The results showed that the impact of PCB emissions into the river is higher in summer than in other seasons due to the low flow rate of the river during this period. P,olar organic chemical integrative samplers (POCIS) were deployed for 4 months in the Sion-Riddes canal (VS) to investigate herbicides (terbuthylazine, diuron and linuron). Desisopropylatrazine-d5 (DIA-d5) was tested as a performance reference compound (PRC) to estimate aqueous concentration. The results showed an increase of water contamination due to the studied agricultural area. The maximal contamination was observed in April and corresponds to the period of herbicide application on the crops.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Validation of methane measurement using headspace-GC-MS and quantification by a stable isotope-labeled internal standard generated in situ.

A previous study has shown the possibility to identify methane (CH4 ) using headspace-GC-MS and quantify it with a stable isotope as internal standard. The main drawback of the GC-MS methods discussed in literature for CH4 measurement is the absence of a specific internal standard necessary to perform quantification. However, it becomes essential to develop a safer method to limit the manipulation of gaseous CH4 and to precisely control the injected amount of gas for spiking and calibration by comparison with external calibration. To avoid the manipulation of a stable isotope-labeled gas, we have chosen to generate a labeled gas as an internal standard in a vial on the basis of the formation of CH4 by the reaction of Grignard reagent methylmagnesium chloride with deuterated water. This method allows precise measurement of CH4 concentrations in gaseous sample as well as in a solid or a liquid sample after a thermodesorption step in a headspace vial. A full accuracy profile validation of this method is then presented.

Pollution stress on aquatic microbial communities

Thousands of chemical compounds enter the natural environment but many have unknown effects and consequences, in particular at low concentrations. This thesis work contributes to our understanding of pollution effects by using bacteria as test organisms. Bacteria are important for this question because some of them degrade and transform pollutants into less harmful compounds, but secondly because they themselves can be inhibited in their reproduction by exposure to toxic compounds. When inhibitory effects occur this may change the composition of the microbial com¬munity in the long run, leading to altered or diminished ecosystem services by those communities. As a result chemicals of anthropogenic origin may accumulate and per¬sist in the environment, and finally, affect higher organisms as well. In addition to acquiring basic understanding of pollutant effects at low concentrations on bacterial communities an applied goal of this thesis work was to develop bacteria-based tests to screen new organic chemicals for toxicity and biodégradation. In the first part of this work we developed a flow cytometry-based assay on SYT09 plus ethidium-bromide or propidium-iodide stained cells of Pseudomonas ûuorescens exposed or not to a variety of pollutants under oligotrophic growth conditions. Flow cytometry (FC) allows fast and accurate counting of bacterial cells under simul¬taneous assessment of their physiological state, in particular in combination with different fluorescent dyes. Here we employed FC and fluorescent dyes to monitor the effect that pollutants may exert on Pseudomonas ûuorescens SV3. First we designed an oligotrophic growth test, which enabled us to follow population growth at low densities (104 - 10 7 cells per ml) using 0.1 mM sodium acetate as carbon source. Cells in the oligotrophic milieu were then exposed or not to a variety of common pollutants, such as 2-chlorobiphenyl (2CBP), naphthalene (NAH), 4-chlorophenol (4CP), tetradecane (TD), mercury chloride (HgCl2) or benzene, in different dosages. Exposed culture samples were stained with SYT09 (green fluorescent dye binding nucleic acids, generally staining all cells) in combination with propidium iodide (PI) or ethidium bromide (EB), both dyes being membrane integrity indicators. We ob- served that most of the tested compounds decreased population growth in a dosage- dependent manner. SYT09/PI or SYT09/EB staining then revealed that chemical exposure led to arisal of subpopulations of live and injured or dead cells. By modeling population growth on the total cell numbers in population or only the subpopulation of live cells we inferred that even in stressed populations live cells multiply at rates no different to unexposed controls. The net decrease in population growth would thus be a consequence of more and more cells being not able to multiply at all, rather than all cells multiplying at slower rates. In addition, the proportion of injured cells correlated to the compound dosage. We concluded that the oligotrophic test may be useful to asses toxicity of unknown chemicals on a variety of model bacteria. Mul¬tiple tests can be run in parallel and effects are rapidly measured within a period of 8 hours. Interestingly, in the same exposure tests with P. fluorescens SV3 we observed that some chemicals which did not lead to a reduction of net population growth rates did cause measurable effects on live cells. This was mainly observed in cells within the live subpopulation as an increase of the EB fluorescence signal. We showed that SYT09/EB is a more useful combination of dyes than SYT09/PI because PI fluorescence tend to increase only when cells are effectively dead, but not so much in live cells (less then twofold). In contrast, EB geometric mean fluorescence in live cells increased up to eightfold after exposure to toxic compounds. All compounds even at the lowest concentration caused a measurable increase in EB geometric mean fluorescence especially after 2 h incubation time. This effect was found to be transient for cells exposed to 2CBP and 4CP, but chronic for cells incubated with TD and NAH (ultimately leading to cell death). In order to understand the mechanism underlying the observed effects we used known membrane or energy uncouplers. The pattern of EB signal increase in chemical-exposed populations resembled mostly that of EDTA, although EB fluorescence in EDTA-treated or pasteurized cells was even higher than after exposure to the four test chemicals. We conclude that the ability of cells to efflux EB under equilibrium conditions is an appropriate measure for the potential of a chemical to exert toxicity. Since most bacterial species possess efflux systems for EB that all require cellular energy, our test should be more widely relevant to infer toxicity effects of chemical exposure on the physiological status of the bacterial cell. To better understand the effect of toxicant exposure on efflux defense systems, we studied 2-hydroxybiphenyl toxicity to Pseudomonas azeiaica HBP1. We showed that 2-HBP exerts toxicity even to P. azelaica HBP1, but only at concentrations higher than 0.5 mM. Above this concentration transient loss of membrane polarization and integrity occurred, which we conclude from staining of growing cells with fluorescent dyes. Cells finally recover and resume growth on 2HBP. The high resistance of P. azelaica HBP1 to 2-HBP was found to be the result of an efficient MexABOprM- type efflux pump system counteracting passive influx of this compound into the membrane and cellular interior. Mutants with disrupted mexA, mexB and oprM genes did no longer grow on 2-HBP at concentrations above 100 μΜ, whereas below this concentration we found 2-HBP-concentration dependent decrease of growth rate. The MexAB-OprM system in P. azeiaica HBP1 is indeed an efflux pump for ethidium bromide as well. By introducing gfp reporter fusions responsive to intracellular 2- HBP concentrations into HBP1 wild-type or the mutants we demonstrated that 2HBP enters into the cells in a similar way. In contrast, the reporter system in the wild-type cells does not react to 2-HBP at an outside concentration of 2.4 μΜ, whereas in mutant cells it does. This suggests that wild-type cells pump 2-HBP to the outside very effectively preventing accumulation of 2-HBP. 2HBP metabolism, therefore, is not efficient enough to lower the intracellular concentration and prevent toxicity. We conclude that P. azelaica HBP1 resistance to 2-HBP is mainly due to an efficient efflux system and that 2HBP in high concentrations exerts narcotic effects on the bacterial membrane. In the part of this thesis, we investigated the possibilities of bacteria to degrade pollutants at low concentrations (1 mg per L and below). As test components we used 2-hydroxybiphenyl, antibiotics and a variety of fragrances, many of which are known to be difficult to biodegrade. By using accurate counting of low numbers of bacterial cells we could demonstrate that specific growth on these compounds is possible. We demonstrated the accuracy of FC counting at low cell numbers (down to 103 bacterial cells per ml). Then we tested whether bacterial population growth could be specifically monitored at the expense of low substrate concentrations, us¬ing P. azelaica HBP1. A perfect relationship was found between growth rate, yield and 2-HBP concentrations in the range of 0.1 up to 5 mg per L. Mixing P. azelaica within sludge, however, suggested that growth yields in a mixed community can be much lower than in pure culture, perhaps because of loss of metabolic intermediates. We then isolated new strains from activated sludge using 2-HBP or antibiotics (Nal, AMP, SMX) at low concentrations (0.1-1 mg per L) as sole carbon and energy sub¬strate and PAO microdishes. The purified strains were then examined for growth on their respective substrate, which interestingly, showed that all strains can not with¬stand higher than 1 or 10 mg per L concentrations of target substrate. Thus, bacteria must exist that contribute to compound degradation at low pollutant concentrations but are inhibited at higher concentrations. Finally we tested whether specific biomass growth (in number of cells) at the expense of pollutants can also be detected with communities as starting material. Hereto, we focused on a number of fragrance chemicals and measured community biomass increase by flow cytometry cell counting on two distinct starter communities: (i) diluted Lake Geneva water, and dilute activated sludge from a wastewater treatment plant. We observed that most of the test compounds indeed resulted in significant biomass increase in the starter community compared to a no-carbon added control, but activated sludge and lake Geneva water strongly differed (almost mutually ex¬clusive) in their capacity to degrade the test chemicals. In two cases for activated sludge the same type of microbial community developed upon compound exposure, as concluded from transcription fragment length polymorphism analysis on community purified and PCR amplified 16S rRNA gene fragments. To properly test compound biodegradability it is thus important to use starter communities of different origin. We conclude that FC counting can be a valuable tool to screen chemicals for their biodegradability and toxicity. - Des milliers de produits chimiques sont libérés dans l'environnement mais beaucoup ont des effets inconnus, en particulier à basses concentrations. Ce travail de thèse contribue à notre comprehension des effets de la pollution en utilisant des bacteries comme des organismes-tests. Les bacteries sont importantes pour etudier cette ques¬tion car certaines d'entre elles peuvent degrader ou transformer les polluants, mais également parce qu'elles-mmes peuvent tre inhibees dans leur reproduction après avoit ete exposees à ces composes toxiques. Quand des effets inhibiteurs ont lieu, la composition de la communauté microbienne peut tre changee à long terme, ce qui mène à une reduction du service d'ecosystème offert par ces communautés. En consequence, après leur liberation dans l'environnement, les produits chimiques d'origine anthropogenique peuvent soit s'y accumuler et per¬sister, exerant ainsi des effets encore inconnus sur les organismes vivants. En plus d'acquérir des connaissances de base sur les effets des polluants à basses concentra¬tions sur les communautés microbiennes, un but applique de cette thèse était de développer des tests bases sur les bacteries afin d'identifier de nouveau composes pour leur toxicité ou leur biodégradation. Dans la première partie de ce travail, nous avons developpe un test base sur la cytometrie de flux (FC) sur des cellules de Pseudomonas fluorescens colorees par du bromure d'ethidium ou de l'iodure de propidium et exposees ou non à une palette de polluants sous des conditions de croissance oligotrophique. La cytometrie de flux est une technique qui connaît de nombreuses applications dans la microbiologie environ¬nementale. Cela est principalement du au fait qu'elle permet un comptage rapide et precis ainsi que l'évaluation de l'état physiologique, en particulier lorsqu'elle est combinée h des colorations fluorescentes. Ici, nous avons utilise la technique FC et des colorants fluorescents afin de mesurer l'effet que peuvent exercer certains pollu¬ants sur Pseudomonas ûuorescens SV3 . D'abord nous avons conu des tests oligo- trophiques qui nous permettent de suivre la croissance complète de cellules en culture h des densites faibles (104 -10 7 cellules par ml), sur de l'acetate de sodium à 0.1 mM, en presence ou absence de produits chimiques (2-chlorobiphenyl (2CBP), naphthalène (NAH), 4-chlorophenol (4CP), tetradecane (TD), chlorure de mercure(II) (HgCl2)) à différentes concentrations. Afin de montrer le devenir des bacteries tant au niveau de la cellule individuelle que celui de la population globale, après exposition à des series de composes chimiques, nous avons compte les cellules colorees avec du SYT09 (col¬orant fluorescent vert des acides nucléiques pour la discrimination des cellules par rapport au bruit de fond) en combinaison avec l'iodure de propidium (PI) ou le bromure d'ethidium (EB), indicateurs de l'intégrité de la membrane cellulaire avec FC. Nous avons observe que de nombreux composes testes avaient un effet sur la croissance bacterienne, resultant en une baisse du taux de reproduction de la pop¬ulation. En outre, la double coloration que nous avons utilisee dans cette etude SYT09/PI ou SYT09/EB a montre que les produits chimiques testes induisaient une reponse heterogène des cellules dans la population, divisant celle-ci en sous- populations "saine", "endommagee" ou "morte". Les nombres de cellules à partir du comptage et de la proportion de celles "saines" et "endommagees/mortes" ont ensuite ete utilises pour modeliser la croissance de P. ûuorescens SV3 exposee aux produits chimiques. La reduction nette dans la croissance de population est une consequence du fait que de plus en plus de cellules sont incapables de se reproduire, plutt que du fait d'une croissance plus lente de l'ensemble de la population. De plus, la proportion de cellules endommagees est correllee au dosage du compose chimique. Les résultats obtenus nous ont permis de conclure que le test oligotrophique que nous avons developpe peut tre utilise pour l'évaluation de la toxicité de produits chimiques sur différents modèles bacteriens. Des tests multiples peuvent tre lances en parallèle et les effets sont mesures en l'espace de huit heures. Par ailleurs, nous en déduisons que les produits chimiques exercént un effet sur la croissance des cellules de P. ûuorescens SV3, qui est heterogène parmi les cellules dans la population et depend du produit chimique. Il est intéressant de noter que dans les mmes tests d'exposition avec P. ûuorescens SV3, nous avons observe que certains composes qui n'ont pas conduit à une reduction du taux de la croissance nette de la population, ont cause des effets mesurables sur les cellule saines. Ceci a ete essentiellement observe dans la portion "saine" des cellules en tant qu'augmentation du signal de la fluorescence de 1ΈΒ. D'abord nous avons montre que SYT09/EB était une com¬binaison de colorants plus utile que celle de SYT09/PI parce que la fluorescence du PI a tendance à augmenter uniquement lorsque les cellules sont effectivement mortes, et non pas dans les cellules saines (moins de deux fois plus). Par opposi¬tion, la fluorescence moyenne de l'EB dans les cellules saines augmente jusqu'à huit fois plus après exposition aux composes toxiques. Tous les composes, mme aux plus basses concentrations, induisent une augmentation mesurable de la fluorescence moy¬enne de 1ΈΒ, plus particulièrement après deux heures d'incubation. Cet effet s'est revele tre transitoire pour les cellules exposees aux 2CNP et 4CP, mais est chro¬nique pour les cellules incubees avec le TD et le NAH (entranant la mort cellulaire). Afin de comprendre les mécanismes qui sous-tendent les effets observes, nous avons utilise des decoupleurs d'energie ou de membrane. L'augmentation du signal EB dans les populations causee par des produits chimiques ressemblait à celle exerce par le chelateur des ions divalents EDTA. Cependant, les intensités du signal EB des cellules exposees aux produits chimiques testees n'ont jamais atteint les valeurs des cellules traitees avec l'EDTA ou pasteurises. Nous en concluons que le test oli- gotrophique utilisant la coloration (SYT09/)EB des cellules exposees ou non à un produit chimique est utile afin d'evaluer l'effet toxique exerce par les polluants sur la physiologie bacterienne. Afin de mieux comprendre la reaction d'un système de defense par pompe à efflux après exposition à une toxine, nous avons étudié la toxicité du 2-hydroxybiphenyl (2-HBP) sur Pseudomonas azeiaica HBP1. Nous avons montre que le 2-HBP exerce une toxicité mme sur HBP1, mais uniquement à des concentrations supérieures à 0.5 mM. Au-dessus de cette concentration, des pertes transitoires d'intégrité et de polarization membranaire ont lieu, comme cela nous a ete montre par coloration des cellules en croissance. Les cellules sont finalement capables de se rétablir et de reprendre leur croissance sur 2-HBP. La forte resistance de P. azeiaica HBP1 h 2-HBP physiologie bacterienne s'est revele tre le résultat d'un système de pompe h efflux de type MexABOprM qui contre-balance l'influx passif de ce compose h travers la membrane. Nous avons montre, en construisant des mutants avec des insertions dans les gènes mexA, mexB and oprM et des fusions avec le gène rapporteur gfp, que l'altération de n'importe quelle partie du système d'efflux conduisait à accroître l'accumulation de 2-HBP dans la cellule, en comparaison avec la souche sauvage HBP1, provoquant une diminution de la resistance au 2-HBP ainsi qu'une baisse du taux de reproduction des cellules. Des systèmes d'efflux similaires sont répandus chez de nombreuses espèces bactériennes. Ils seraient responsables de la resistance aux produits chimiques tels que les colorants fluorescents (bromure d'ethidium) et des antibiotiques. Nous concluons que la resistance de P. azelaica HBP1 à 2-HBP est principalement due à un système d'efflux efficace et que 2-HBP, à des concentrations elevees, exerce un effet deletère sur la membrane bacterienne. En se basant sur le comptage des cellules avec la FC, nous avons developpe ensuite une methode pour evaluer la biodegradabilite de polluants tels que le 2-HBP ainsi que les antibiotiques (acide nalidixique (Nal), ampicilline (AMP) ou sulfamethoxazole (SMX)) à de faibles concentrations lmg par L et moins), par le suivi de la croissance spécifique sur le compose de cultures microbiennes pures et mixtes. En utilisant un comptage precis de faibles quantités de cellules nous avons pu demontrer que la croissance spécifique sur ces composes est possible. Nous avons pu illustrer la precision du comptage par cytometrie de flux à faible quantité de cellules (jusqu'à 10 3 cellules par ml). Ensuite, nous avons teste s'il était possible de suivre dynamiquement la croissance de la population de cellules sur faibles concentrations de substrats, en utilisant P. azelaica HBP1. Une relation parfaite a ete trouvee entre le taux de croissance, le rendement et les concentrations de 2-HBP (entre 0.1 et 5 mg par L). En mélangeant HBP1 à de la boue active, nous avons pu montrer que le rendement en communauté mixtes pouvait tre bien inférieur qu'en culture pure. Ceci étant peut tre le résultat d'une perte d'intermédiaires métaboliques. Nous avons ensuite isole de nouvelles souches à partir de la boue active en utilisant le 2-HBP ou des antibiotiques (Nal, AMP, SMX) h basses concentrations (0.1-1 mg par L) comme seules sources de carbone et d'energie. En combinaison avec ceci, nous avons également utilise des microplaques PAO. Les souches purifiees ont ensuite ete examinees pour leurs croissances sur leurs substrats respectifs. De faon intéressante, toutes ces souches ont montre qu'elles ne pouvaient pas survivre à des concentrations de substrats supérieures à 1 ou 10 mg par L. Ainsi, il existe des bacteries qui contribuent à la degradation de composes à basses concentrations de polluant mais sont inhibes lorsque ces concentrations deviennent plus hautes. Finalement, nous avons cherche à savoir s'il est possible de detecter une croissance spécifique à une biomasse au depend d'un polluant, en partant d'une communauté microbienne. Ainsi, nous nous sommes concentre sur certains composes et avons mesure l'augmentation de la biomasse d'une communauté grce à la cytometrie de flux. Nous avons compte deux communautés de depart distinctes: (i) une dilution d'eau du Lac Léman, et une dilution de boue active d'une station d'épuration. Nous avons observe que la plupart des composes testes ont entrane une augmentation de la biomasse de depart par rapport au control sans addition de source de carbone. Néanmoins, les échantillons du lac Léman et de la station d'épuration différaient largement (s'excluant mutuellement l'un l'autre) dans leur capacité à degrader les composes chimiques. Dans deux cas provenant de la station d'épuration, le mme type de communauté microbienne s'est developpe après exposition aux composes, comme l'a démontré l'analyse TRFLP sur les fragments d'ARN 16S purifie de la communauté et amplifie par PCR. Afin de tester correctement la biodegradabilite d'un compose, il est donc important d'utiliser des communautés de depart de différentes origines Nous en concluons que le comptage par cytometrie de flux peut tre un outil de grande utilité pour mettre en valeur la biodegradabillite et la toxicité des composes chimiques.

Front-crawl instantaneous velocity estimation using a wearable inertial measurement unit.

Monitoring the performance is a crucial task for elite sports during both training and competition. Velocity is the key parameter of performance in swimming, but swimming performance evaluation remains immature due to the complexities of measurements in water. The purpose of this study is to use a single inertial measurement unit (IMU) to estimate front crawl velocity. Thirty swimmers, equipped with an IMU on the sacrum, each performed four different velocity trials of 25 m in ascending order. A tethered speedometer was used as the velocity measurement reference. Deployment of biomechanical constraints of front crawl locomotion and change detection framework on acceleration signal paved the way for a drift-free integration of forward acceleration using IMU to estimate the swimmers velocity. A difference of 0.6 ± 5.4 cm · s(-1) on mean cycle velocity and an RMS difference of 11.3 cm · s(-1) in instantaneous velocity estimation were observed between IMU and the reference. The most important contribution of the study is a new practical tool for objective evaluation of swimming performance. A single body-worn IMU provides timely feedback for coaches and sport scientists without any complicated setup or restraining the swimmer's natural technique.

Bacterial bioassay for rapid and accurate analysis of arsenic in highly variable groundwater samples.

In this study, we report the first ever large-scale environmental validation of a microbial reporter-based test to measure arsenic concentrations in natural water resources. A bioluminescence-producing arsenic-inducible bacterium based on Escherichia coli was used as the reporter organism. Specific protocols were developed with the goal to avoid the negative influence of iron in groundwater on arsenic availability to the bioreporter cells. A total of 194 groundwater samples were collected in the Red River and Mekong River Delta regions of Vietnam and were analyzed both by atomic absorption spectroscopy (AAS) and by the arsenic bioreporter protocol. The bacterial cells performed well at and above arsenic concentrations in groundwater of 7 microg/L, with an almost linearly proportional increase of the bioluminescence signal between 10 and 100 microg As/L (r2 = 0.997). Comparisons between AAS and arsenic bioreporter determinations gave an overall average of 8.0% false negative and 2.4% false positive identifications for the bioreporter prediction at the WHO recommended acceptable arsenic concentration of 10 microg/L, which is far betterthan the performance of chemical field test kits. Because of the ease of the measurement protocol and the low application cost, the microbiological arsenic test has a great potential in large screening campaigns in Asia and in other areas suffering from arsenic pollution in groundwater resources.