Claude Durrieu

Optical whole-cell biosensor using Chlorella vulgaris designed for monitoring herbicides

An optical biosensor was designed for determination of herbicides as aquatic contaminants. Detection was obtained with immobilised Chlorella vulgaris microalgae entrapped on a quartz microfibre filter and placed in a five-membrane-home-made-flow cell. The algal chlorophyll fluorescence modified by the presence of herbicides was collected at the tip of an optical fibre bundle and sent to a fluorimeter. A continuous culture was set up to produce algal cells in reproducible conditions for measurement optimisation. Effects of flow rate, algal density, temperature, and pH on the biosensor response to atrazine were studied. Reversibility and detection limits were determined for DNOC and atrazine, simazine, isoproturon, diuron. Detection of photosystem II (PSII) herbicides was achieved at sub-ppb concentration level.

Synchronous-scan fluorescence of algal cells for toxicity assessment of heavy metals and herbicides

Synchronous-scan spectrofluorometry was applied to Chlorella vulgaris cells to assess the toxicity of heavy metals and herbicides in water. Simultaneous scan of both the excitation and emission spectra was done at a constant wavelength difference Deltalambda (20-140 nm) between the emission and excitation wavelengths in the range of 420-700 nm emission, where a peak of fluorescence was observed. Its position depends on Deltalambda. Fluorescence measurements were conducted with algal cells in suspension in water and immobilized in a translucent silica matrix. The influence of toxic chemicals was tested with cadmium as a heavy metal and with atrazine, diuron, DNOC and paraquat as herbicides. The toxic effect of those chemicals mainly results in a quenching of algal cells fluorescence by reducing their photosynthetic activity.

Development of a Biosensor for Environmental Monitoring Based on Microalgae Immobilized in Silica Hydrogels

A new biosensor was designed for the assessment of aquatic environment quality. Three microalgae were used as toxicity bioindicators: Chlorella vulgaris, Pseudokirchneriella subcapitata and Chlamydomonas reinhardtii. These microalgae were immobilized in alginate and silica hydrogels in a two step procedure. After studying the growth rate of entrapped cells, chlorophyll fluorescence was measured after exposure to (3-(3,4-dichlorophenyl)-1,1-dimethylurea) (DCMU) and various concentrations of the common herbicide atrazine. Microalgae are very sensitive to herbicides and detection of fluorescence enhancement with very good efficiency was realized. The best detection limit was 0.1 μM, obtained with the strain C. reinhardtii after 40 minutes of exposure.

A dialysis system with phytoplankton for monitoring chemical pollution in freshwater ecosystems by alkaline phosphatase assay

The effects of three groups of chemicals, ‘heavy’ metals, pesticides and phenolics, on alkaline phosphatase activity of intact Chlorella vulgaris cells were investigated. There was a marked inhibitory effect of heavy metals and a slight one due to phenolics, but the pesticides tested showed no effect. In order to detect heavy metals in freshwater ecosystems, we propose a dialysis system, which can be placed in the field and then provide early warning signals of toxicity. This phosphatase inhibition test is recommended the first stage of an enzymatic screening system for chemical pollution in water.

Sol-gel silica platforms for microalgae-based optical biosensors

An advanced hybrid biosensing platform with improved optical quality is developed based on the acidic encapsulation of microalgi in silica matrices synthesized by TAFR (tetraethoxysilane derived alcohol free route). The three microalgi (Chlorella vulgaris, Pseudokirchneriella subcapitata and Chlamydomonas reinhardtii) were previously immobilized in alginate following the two-step procedure. Tuning the alginate protecting function with the aid of Tris-HCl buffer, the sol-gel synthesis was conducted at pH 4.0 well below the tolerance limit imposed by the encapsulated microalgae. The acidic condensation of Si(IV) generates silica matrices with outstanding optical properties that suit the requirements of biosensors based on optical detection methods.

A Bi‐enzymatic Whole‐Cell Algal Biosensor for Monitoring Waste Water Pollutants

Abstract Two algal whole cells biosensors are developed to measure specific toxicity of freshwater pollutants. Both optical and conductometric biosensors are based on inhibition of algal alkaline phosphatase (AP) and esterase activities. Chlorella vulgaris cells are immobilised on a membrane placed in front of an optical fiber bundle for optical sensing or deposited on the surface of an electrode for conductometric sensing. Phosphatase activity of the biosensor is strongly inhibited by heavy metal ions (60% loss of activity is obtained after 10 ppb Cd2+ and Zn2+ with 20 min exposure time), as equally observed with a microplate reader. Inhibition of esterase activity (EA) is actually achieved with organophosphorous pesticides such as methyl paraoxon. The biosensors exhibit a response time of about 5 min. These pollutants can be detected down to 10 ppb after being in contact with the biosensor for 30 min. The biosensor can be used up to 20 days with 90% remaining activity.

Methods for evaluating the pollution impact of urban wet weather discharges on biocenosis: A review.

Rainwater becomes loaded with a large number of pollutants when in contact with the atmosphere and urban surfaces. These pollutants (such as metals, pesticides, PAHs, PCBs) reduce the quality of water bodies. As it is now acknowledged that physico-chemical analyses alone are insufficient for identifying an ecological impact, these analyses are frequently completed or replaced by impact studies communities living in freshwater ecosystems (requiring biological indices), ecotoxicological studies, etc. Thus, different monitoring strategies have been developed over recent decades aimed at evaluating the impact of the pollution brought by urban wet weather discharges on the biocenosis of receiving aquatic ecosystems. The purpose of this review is to establish a synthetic and critical view of these different methods used, to define their advantages and disadvantages, and to provide recommendations for futures researches. Although studies on aquatic communities are used efficiently, notably on benthic macroinvertebrates, they are difficult to interpret. In addition, despite the fact that certain bioassays lack representativeness, the literature at present appears meagre regarding ecotoxicological studies conducted in situ. However, new tools for studying urban wet weather discharges have emerged, namely biosensors. The advantages of biosensors are that they allow monitoring the impact of discharges in situ and continuously. However, only one study on this subject has been identified so far, making it necessary to perform further research in this direction.

Tamoxifen ecotoxicity and resulting risks for aquatic ecosystems

Tamoxifen, a drug used to treat cancer, is regularly found in hydrosystems at concentrations of several hundred ng L(-1). To characterize its ecotoxicity, we implemented a battery of bioassays on organisms belonging to 3 different trophic levels: Pseudokirchneriella subcapitata, Chlorella vulgaris and Chlamydomonas reinhardtii, for primary producers, Daphnia magna (immobilization, grazing and reproduction) for primary consumers, and Danio rerio for secondary consumers (embryotoxicity test). In view of the results obtained and the ecotoxicity values of tamoxifen available in the literature, we established a PNEC (Predictive No Effect Concentration) equal to 81 ng L(-1) for continental water. This PNEC allowed us to calculate Risk Quotients (RQ) for 4 continental hydrosystems in 4 different countries in which measures of tamoxifen had already been performed on surface waters. In two of the situations studied, RQs were higher than 1, reaching a maximum of 2.6. These results show the need to deepen the characterization of ecotoxicological risks linked to the discharge of tamoxifen in surface waters. In addition, we propose applying this approach to other drug residues detected in the environment.

Unicellular algae used as biosensors for chemical detection in Mediterranean lagoon and coastal waters.

Lagoons and coastal waters are contaminated by a large number of chemicals discharged directly or carried by rivers and runoff water that drain catchment areas in which agricultural activities take place. The inflow of these exogenous compounds constitutes a genuine risk for the health of ecosystems. It is therefore important to detect their presence in the natural environment before they cause irreversible damage. Here we present a study aimed at developing a tool for rapid detection of pesticides and other chemicals in environments liable to be contaminated, in order to propose an early warning system for decision-makers. The study carried out focuses on two herbicides commonly encountered in the environment, i.e. diuron and glyphosate, as well as several of their photodegradation products (DCPU, DCPMU, AMPA). The results presented contribute toward developing a biosensor based on measuring the metabolic activities of immobilized unicellular marine algae. The sensors operation is based on measuring the esterase localized on the external membrane of the algae cells and chlorophyll fluorescence. The tests carried out show that the signal emitted by the sensor is disturbed by the presence of the two herbicides studied. The system proposed appears useful as a tool for controlling environments requiring monitoring.

Extracting Decision Rules from Qualitative Data Using Sugeno Integral: A Case-Study

This paper deals with knowledge extraction from experimental data in multifactorial evaluation using Sugeno integrals. They are qualitative criteria aggregations where it is possible to assign weights to groups of criteria. A method for deriving such weights from data is recalled. We also present results in the logical representation of Sugeno integrals. Then we show how to extract if-then rules expressing the selection of good situations on the basis of local evaluations, and rules to detect bad situations. We illustrate such methods on a case-study in the area of water ecosystem health.