Development and validation of a multiresidue method for the analysis of more than 500 pesticides and drugs in water based on on-line and liquid chromatography coupled to high resolution mass spectrometry.

Screening of a large number of emerging pollutants is highly desirable for the control of water quality. In this respect, a novel, fully automated contaminant screening method based on an integrated sample preconcentration and liquid chromatography coupled to high resolution mass spectrometry (SPE-UHPLC-HRMS) has been developed. The optimal chromatographic column and experimental conditions allowing the retention and subsequent elution of the maximum number of analytes were defined. Liquid chromatography and Q-exactive (Orbitrap™) parameters were optimized to obtain the best separation of molecules of interest, and the lowest detection limits. Due to the large amount of data to compare, a script written in R language was developed to evaluate the quality of the data generated by the comparison of 14 experimental conditions. The developed method enables the simultaneous semi quantitative analysis of 539 compounds (pesticides and drug residues), in 36 min with only 5 mL of water. Method validation was achieved through studies of repeatability, selectivity, linearity and matrix effect. Application to 20 tap water samples collected in and around Paris showed the presence of 34 different compounds all with concentrations below 0.1 µg/L, the European Union limit for drinking water. Pesticides and transformation products frequently found in water resources such as atrazine and its metabolites, hexazinone, oxadixyl, propazine and simazine were detected. Drug residues such as valsartan and carbamazepine, usually not monitored, were also found. The next step will be to assess the ability of this method to highlight the presence of unexpected contaminants not present in our database.

Annotation of the Staphylococcus aureus Metabolome Using Liquid Chromatography Coupled to High-Resolution Mass Spectrometry and Application to the Study of Methicillin Resistance.

Staphylococcus aureus can cause a variety of severe disease patterns and can readily acquire antibiotic resistance; however, the mechanisms by which this commensal becomes a pathogen or develops antibiotic resistance are still poorly understood. Here we asked whether metabolomics can be used to distinguish bacterial strains with different antibiotic susceptibilities. Thus, an efficient and robust method was first thoroughly implemented to measure the intracellular metabolites of S. aureus in an unbiased and reproducible manner. We also placed special emphasis on metabolome coverage and annotation and used both hydrophilic interaction liquid chromatography and pentafluorophenyl-propyl columns coupled to high-resolution mass spectrometry in conjunction with our spectral database developed in-house to identify with high confidence as many meaningful S. aureus metabolites as possible. Overall, we were able to characterize up to 210 metabolites in S. aureus, which represents a substantial ∼50% improvement over previously published data. We then preliminarily compared the metabolic profiles of 10 clinically relevant methicillin-resistant and susceptible strains harvested at different time points during the exponential growth phase (without any antibiotic exposure). Interestingly, the resulting data revealed a distinct behavior of "slow-growing" resistant strains, which show modified levels of several precursors of peptidoglycan and capsular polysaccharide biosynthesis.

High-resolution mass spectrometry associated with data mining tools for the detection of pollutants and chemical characterization of honey samples.

Analytical methods for food control are mainly focused on restricted lists of well-known contaminants. This paper shows that liquid chromatography-high-resolution mass spectrometry (LC/ESI-HRMS) associated with the data mining tools developed for metabolomics can address this issue by enabling (i) targeted analyses of pollutants, (ii) detection of untargeted and unknown xenobiotics, and (iii) detection of metabolites useful for the characterization of food matrices. A proof-of-concept study was performed on 76 honey samples. Targeted analysis indicated that 35 of 83 targeted molecules were detected in the 76 honey samples at concentrations below regulatory limits. Furthermore, untargeted metabolomic-like analyses highlighted 12 chlorinated xenobiotics, 1 of which was detected in lavender honey samples and identified as 2,6-dichlorobenzamide, a metabolite of dichlobenil, a pesticide banned in France since 2010. Lastly, multivariate statistical analyses discriminated honey samples according to their floral origin, and six discriminating metabolites were characterized thanks to the MS/MS experiments.

Investigating the plant response to cadmium exposure by proteomic and metabolomic approaches.

Monitoring molecular dynamics of an organism upon stress is probably the best approach to decipher physiological mechanisms involved in the stress response. Quantitative analysis of proteins and metabolites is able to provide accurate information about molecular changes allowing the establishment of a range of more or less specific mechanisms, leading to the identification of major players in the considered pathways. Such tools have been successfully used to analyze the plant response to cadmium (Cd), a major pollutant capable of causing severe health issues as it accumulates in the food chain. We present a summary of proteomics and metabolomics works that contributed to a better understanding of the molecular aspects involved in the plant response to Cd. This work allowed us to provide a finer picture of general signaling, regulatory and metabolic pathways that appeared to be affected upon Cd stress. In particular, we conclude on the advantage of employing different approaches of global proteome- and metabolome-wide techniques, combined with more targeted analysis to answer molecular questions and unravel biological networks. Finally, we propose possible directions and methodologies for future prospectives in this field, as many aspects of the plant-Cd interaction remain to be discovered.

Mass spectrometry for the identification of the discriminating signals from metabolomics: current status and future trends.

The metabolome is characterized by a large number of molecules exhibiting a high diversity of chemical structures and abundances, requiring complementary analytical platforms to reach its extensive coverage. Among them, atmospheric pressure ionization mass spectrometry (API-MS)-based technologies, and especially those using electrospray ionization are now very popular. In this context, this review deals with strengths, limitations and future trends in the identification of signals highlighted by API-MS-based metabolomics. It covers the identification process from the determination of the molecular mass and/or its elemental composition to the confirmation of structural hypotheses. Furthermore, some tools that were developed in order to address the MS signal redundancy and some approaches that could facilitate identification by improving the visualization and organization of complex data sets are also reported and discussed.

The early responses of Arabidopsis thaliana cells to cadmium exposure explored by protein and metabolite profiling analyses.

To get more insight into plant cell response to cadmium (Cd) stress, both proteomic and metabolomic "differential display" analyses were performed on Arabidopsis thaliana cells exposed to different concentrations of the toxic chemical. After a 24 h treatment, soluble proteins extracted from untreated and treated cells were separated by 2-D-PAGE and image analyses were performed to quantify and compare protein levels. Proteins up- and down-regulated in response to Cd were identified by MS and mapped into specific metabolic pathways and cellular processes, highlighting probable activation of the carbon, nitrogen, and sulfur metabolic pathways. For some of these proteins, Northern blot and RT-PCR analyses were performed to test transcript accumulation in response to Cd. In parallel, metabolite profiling analyses by LC coupled to ESI MS were initiated to better characterize the metabolic adaptation to the chemical stress. This study revealed that the main variation at the metabolite level came from the presence of six different families of phytochelatins, in A. thaliana cells treated with Cd, whose accumulation increases with Cd concentrations. Taken together these data provide an overview of the molecular and cellular changes elicited by Cd exposure.