Carine Arnaudguilhem

Multi-residue analysis and ultra-trace quantification of 36 priority substances from the European Water Framework Directive by GC-MS and LC-FLD-MS/MS in surface waters.

A multi residue analysis was developed for screening, quantification and confirmation of 36 priority organic compounds included in the 2000/60/EC European Water Framework Directive. The compounds analyzed included 19 pesticides, 8 PAH, 5 endocrine-disruptors and 4 organochlorine compounds. The method was developed in three steps. First, automated off-line solid-phase extraction using Strata X cartridges was optimized to trap simultaneously the 36 studied compounds. Second, the more volatile compounds were analysed by gas chromatography coupled to mass spectrometry with electron impact ionisation in selected ion monitoring mode (SIM). Third, the last 20 compounds were detected and quantified, in one run, by liquid chromatography coupled to fluorescence detector and tandem mass spectrometry. The excellent selectivity and sensitivity allowed us satisfactory quantification and confirmation at levels as low as 0.2-67 ng L(-1) with recoveries between 59 and 105%. Such methodology was then applied to French surface waters: all the waters present organic contaminants, and their concentration varied according to the origin and nature of substances.

Discrimination of geographical origin of rice based on multi-element fingerprinting by high resolution inductively coupled plasma mass spectrometry.

Rice is a staple food for nearly half the worlds population. The discrimination of geographical origin of rice in order to its authenticity is essential to prevent mislabeling and adulteration problems. The multi-element fingerprinting has a great potential for the differentiation of rice grains. A study of the capability of the high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) methodology for multi-element fingerprinting of rice has been carried out. A total of 31 Thai jasmine rice and 5 foreign (France, India, Italy, Japan and Pakistan) rice samples were analysed by high resolution ICP-MS after acid digestion. Accuracy of the whole procedure was verified by the analysis of rice flour standard reference material (NIST SRM 1568a). The concentrations of 21 elements were evaluated and used as chemical indicator to discriminate the origin of rice samples. The classification of rice samples was carried out based on elemental composition by a radar plot and multivariate data analysis, including principal component analysis (PCA) and discriminant analysis (DA). Thai jasmine rice can be differentiated from foreign rice samples by radar plots and multivariate data analysis. Furthermore, the DA can differentiate Thai jasmine rice samples according to each region of origin (northern, northeastern or central regions of Thailand). Therefore, multi-element fingerprinting combined with the use of multivariate statistical techniques can be considered as a powerful tool for rice authentication.

Application of TLC and LA ICP SF MS for speciation of S, Ni and V in petroleum samples

A coupling of thin layer chromatography with laser ablation ICP SF MS was developed for the fractionation of Ni, V, Fe and S in crude oil and its fractions (saturate, aromatic, resin and asphaltene). The detection limits were 18 ng g(-1) and 23 ng g(-1) for nickel and vanadium, respectively, and a sample could be characterized in terms of the metal distribution as a function of species polarity within 10 min. The method was used to characterize the metal distribution in crude oils of different origins and their different fractions.

Large-scale speciation of selenium in rice proteins using ICP-MS assisted electrospray MS/MS proteomics

A Se-targeted bottom-up proteomics approach was developed for the identification of Se-containing proteins in rice grown naturally on seleniferous soils. The proteins were separated by 2D gel electrophoresis. The position of Se-containing spots was tentatively identified by the correlation between the 1D isoelectrofocusing (IEF) and 1D SDS electropherograms of a sample aliquot and confirmed by (78)Se imaging in the 2D gel. The method was complemented by the ICP-MS assisted shotgun proteomics approach. The proteins were identified by capHPLC with the dual ICP MS and electrospray Orbitrap MS detection. The first ever comprehensive study of rice selenoproteome revealed the presence of selenium, as both selenomethionine (SeMet) and selenocysteine (SeCys) residues, in a dozen proteins including a 19 kDa globulin, granule-bound starch synthase, and the family of glutelin-type seed storage proteins.

A multi-residue analysis of sulphonamides in edible animal tissues using QuEChERS extraction and HPLC-MS/MS

A HPLC double reaction monitoring MS/MS method was developed for the determination of a wide range (>20) of sulphonamide residues in several edible animal (sheep, pork, beef, chicken and dromedary) tissues. Sample preparation was based on the simultaneous extraction into acetonitrile solution followed by a clean-up using primary secondary amine beads. Quantification was carried out using matrix-matched calibration curves. The limit of detection (LOD) and limit of quantification (LOQ) ranged from 0.5 to 14.5 μg kg−1 and from 1.8 to 48.4 μg kg−1, respectively. The decision limit (CCα) and decision capability (CCβ) obtained were below 100 μg kg−1 for sulphonamides and below 5 μg kg−1 for dapsone. The method was validated in terms of recoveries and inter- and intra-day precision by reference analyses of meat samples using LC-Orbitrap MS and by the analysis of a reference material. The method was applied to the analysis of several animal tissue samples collected in Lebanon. The highest values were observed for sulfamethazine and sulfadimethoxine at 70.2 and 62.5 μg kg−1 in sheep tissues.

Investigation of Elemental Mass Spectrometry in Pharmacology for Peptide Quantitation at Femtomolar Levels

In the search of new robust and environmental-friendly analytical methods able to answer quantitative issues in pharmacology, we explore liquid chromatography (LC) associated with elemental mass spectrometry (ICP-MS) to monitor peptides in such complex biological matrices. The novelty is to use mass spectrometry to replace radiolabelling and radioactivity measurements, which represent up-to now the gold standard to measure organic compound concentrations in life science. As a proof of concept, we choose the vasopressin (AVP)/V1A receptor system for model pharmacological assays. The capacity of ICP-MS to provide highly sensitive quantitation of metallic and hetero elements, whatever the sample medium, prompted us to investigate this technique in combination with appropriate labelling of the peptide of interest. Selenium, that is scarcely present in biological media, was selected as a good compromise between ICP-MS response, covalent tagging ability using conventional sulfur chemistry and peptide detection specificity. Applying selenium monitoring by elemental mass spectrometry in pharmacology is challenging due to the very high salt content and organic material complexity of the samples that produces polyatomic aggregates and thus potentially mass interferences with selenium detection. Hyphenation with a chromatographic separation was found compulsory. Noteworthy, we aimed to develop a straightforward quantitative protocol that can be performed in any laboratory equipped with a standard macrobore LC-ICP-MS system, in order to avoid time-consuming sample treatment or special implementation of instrumental set-up, while allowing efficient suppression of all mass interferences to reach the targeted sensitivity. Significantly, a quantification limit of 57 ng Se L-1 (72 femtomoles of injected Se) was achieved, the samples issued from the pharmacological assays being directly introduced into the LC-ICP-MS system. The established method was successfully validated and applied to the measurement of the vasopressin ligand affinity for its V1A receptor through the determination of the dissociation constant (Kd) which was compared to the one recorded with conventional radioactivity assays.