Développement d’une nouvelle méthode d’analyse multi-résidus par LDTD/APCI-MS/MS pour la quantification de pesticides et de produits pharmaceutiques dans les eaux usées

Une nouvelle méthode d'extraction en phase solide (SPE) couplée à une technique d'analyse ultrarapide a été développée pour la détermination simultanée de neuf contaminants émergents (l'atrazine, le déséthylatrazine, le 17(béta)-estradiol, l'éthynylestradiol, la noréthindrone, la caféine, la carbamazépine, le diclofénac et le sulfaméthoxazole) provenant de différentes classes thérapeutiques et présents dans les eaux usées. La pré-concentration et la purification des échantillons a été réalisée avec une cartouche SPE en mode mixte (Strata ABW) ayant à la fois des propriétés échangeuses de cations et d'anions suivie d'une analyse par une désorption thermique par diode laser/ionisation chimique à pression atmosphérique couplée à la spectrométrie de masse en tandem (LDTD-APCI-MS/MS). La LDTD est une nouvelle méthode d'introduction d'échantillon qui réduit le temps total d'analyse à moins de 15 secondes par rapport à plusieurs minutes avec la chromatographie liquide couplée à la spectrométrie de masse en tandem traditionnelle (LC-MS/MS). Plusieurs paramètres SPE ont été évalués dans le but d'optimiser l'efficacité de récupération lors de l'extraction des analytes provenant des eaux usées, tels que la nature de la phase stationnaire, le débit de chargement, le pH d'extraction, le volume et la composition de la solution de lavage et le volume de l'échantillon initial. Cette nouvelle méthode a été appliquée avec succès à de vrais échantillons d'eaux usées provenant d'un réservoir de décantation primaire. Le recouvrement des composés ciblés provenant des eaux usées a été de 78 à 106%, la limite de détection a été de 30 à 122 ng L-1, alors que la limite de quantification a été de 88 à 370 ng L-1. Les courbes d'étalonnage dans les matrices d'eaux usées ont montré une bonne linéarité (R2 > 0,991) pour les analytes cibles ainsi qu’une précision avec un coefficient de variance inférieure à 15%.A new solid phase extraction (SPE) method coupled to a high throughput sample analysis technique was developed for the simultaneous determination of nine selected emerging contaminants (atrazine, desethylatrazine, 17(beta)-estradiol, ethynylestradiol, northindrone, caffeine, carbamazepine, diclofenac and sulfamethoxazole) comprising drugs from different therapeutic classes present in wastewater. Sample pre-concentration and clean-up was performed with a mixed-mode SPE cartridge (Strata ABW) having both cation and anion exchange properties followed by analysis by laser diode thermal desorption/atmospheric pressure chemical ionization coupled to tandem mass spectrometry (LDTD-APCI-MS/MS). The LDTD is a new high-throughput sample introduction method, which reduces total analysis time to less than 15 seconds compared to minutes with traditional liquid-chromatography coupled to tandem mass spectrometry (LC-MS/MS). Several SPE parameters were evaluated in order to optimize recovery efficiencies when extracting analytes from wastewater, such as the nature of stationary phase, the loading flow rate, the extraction pH, the various volume and composition of the washing solution and the initial sample volume. The method was successfully applied to real wastewater samples from a primary sedimentation tank. Recoveries of target compounds from wastewater ranged from 78 to 106 %, the limit of detection ranged from 30 to 122 ng L-1 while the limit of quantification ranged from 88 to 370 ng L-1. Calibration curves in wastewater matrix showed good linearity (R2 > 0.991), for all target analytes, and precision (intraday and interday) showed a coefficient of variance below 15%

Strategies for Untargeted Biomarker Discovery in Biological Fluids

The health status of an organism modulates the dynamic and complex interplay of biochemical species that make-up the body and fluids of the organism. As such, these biological fluids are routinely used for diagnostic testing, yet they are often not used to their full potential. For instance, amniotic fluid (AF), the fluid that surrounds the fetus during gestation, is collected primarily for genetic testing from women with identified risk factors. The AF proteome and/or metabolome are seldom considered and represent a largely untapped wealth of relevant clinical information. Extensive, multi-analyte data can be collected from biological samples with modern analytical instrumentation. However, sophisticated data preprocessing and analysis (i.e. chemometrics) are required to reveal the relationships between the biochemical signals and the health status. This thesis seeks to demonstrate that untargeted biomarker discovery strategies can be efficiently applied to the task of finding novel biomarkers and complement the traditional hypothesis driven approaches. In the work underlying this thesis, a chemometric data analysis strategy was developed to search for biomarkers in capillary electrophoresis (CE) separations data. The absorbance data from amniotic fluid samples (n=107) collected at 15 weeks gestation, at 195 +/- 4 nm, was normalized, time aligned with Correlation Optimized Warping and reduced to a smaller number of variables by Haar transformation. The reduced data was then classified into normal or abnormal health classes by using a Bayes classifier algorithm. The chemometric data analysis was first employed to find biomarkers of gestational diabetes mellitus (GDM) and revealed that human serum albumin (HSA) could predict the early onset of disease. The same approach was successfully used to identify cases of large-for-gestational age (LGA) with the same AF CE-UV data. It was also employed for the classification of embryos with high and low reproductive potential using in vitro fertilization (IVF) culture media analyzed by CE-UV. Overall, a chemometric method was developed to perform untargeted biomarker discovery in biological samples and provide new means to detect GDM pregnancies, LGA neonates and viable embryos in IVF. The method was successful at identifying biomarkers of interest and showed high flexibility and transferability to other biological fluids

Aven recognition of RNA G-quadruplexes regulates translation of the mixed lineage leukemia protooncogenes

Abstract: G-quadruplexes (G4) are extremely stable secondary structures forming stacks of guanine tetrads. DNA G4 structures have been extensively studied, however, less is known about G4 motifs in mRNAs, especially in their coding sequences. Herein, we show that Aven stimulates the mRNA translation of the mixed lineage leukemia (MLL) proto-oncogene in an arginine methylation-dependent manner. The Aven RGG/RG motif bound G4 structures within the coding regions of the MLL1 and MLL4 mRNAs increasing their polysomal association and translation, resulting in the induction of transcription of leukemic genes. The DHX36 RNA helicase associated with the Aven complex and was required for optimal translation of G4 mRNAs. Depletion of Aven led to a decrease in synthesis of MLL1 and MLL4 proteins resulting in reduced proliferation of leukemic cells. These findings identify an Aven-centered complex that stimulates the translation of G4 harboring mRNAs, thereby promoting survival of leukemic cells