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In this work the effect of chlorpyrifos exposure on metabolic profiles of zebrafish muscle was evaluated by liquid chromatography coupled to high resolution mass spectrometry. Different chemometric tools based on the selection of Regions of Interest and on Multivariate Curve-Resolution-Alternating Least Squares are proposed for the analysis of the complex data sets generated in the different exposure experiments. Analysis of Variance Simultaneous Component Analysis of changes on metabolite peak profile areas showed significant chlorpyrifos concentration and exposure time-dependent changes, clearly differentiating between exposed and non-exposed samples and between short (2 h) and long exposure times (6 h or 24 h). The changes observed in the concentrations of 50 muscle metabolites are indicative of induction of oxidative stress, of a general disruption of neurotransmitter metabolism, and of muscle exhaustion. These three effects are intimately related to the toxicity of chlorpyrifos. © 2016 Elsevier Ltd ; The research leading to these results has received funding from the European Research Council under European Union's Seven Framework Programme (FP/2007-2013)/ERC Grant Agreement n.320737. ; Peer reviewed

Disruption of specific metabolic pathways constitutes the mode of action of many known toxicants and it is responsible for the adverse phenotypes associated to human genetic defects. Conversely, many industrial applications rely on metabolic alterations of diverse microorganisms, whereas many therapeutic drugs aim to selectively disrupt pathogens' metabolism. In this work we analyzed metabolic changes induced by auxotrophic starvation conditions in yeast in a non-targeted approach, using one-dimensional proton Nuclear Magnetic Resonance spectroscopy (1H NMR) and chemometric analyses. Analysis of the raw spectral datasets showed specific changes linked to the different stages during unrestricted yeast growth, as well as specific changes linked to each of the four tested starvation conditions (L-methionine, L-histidine, L-leucine and uracil). Analysis of changes in concentrations of more than 40 metabolites by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) showed the normal progression of key metabolites during lag, exponential and stationary unrestricted growth phases, while reflecting the metabolic blockage induced by the starvation conditions. In this case, different metabolic intermediates accumulated over time, allowing identification of the different metabolic pathways specifically affected by each gene disruption. This synergy between NMR metabolomics and molecular biology may have clear implications for both genetic diagnostics and drug development. © The Author(s) 2016. ; The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 320737. We also thank Dr. Yolanda Pérez for her helpful recommendations on setting up the acquisition parameters for some of the NMR experiments. ; Peer reviewed

There is a growing interest in biological models to investigate the effect of neurotransmitter dysregulation on the structure and function of the central nervous system (CNS) at different stages of development. Zebrafish, a vertebrate model increasingly used in neurobiology and neurotoxicology, shares the common neurotransmitter systems with mammals, including glutamate, GABA, glycine, dopamine, norepinephrine, epinephrine, serotonin, acetylcholine, and histamine. In this study, we have evaluated the performance of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the multiresidue determination of neurotransmitters and related metabolites. In a first step, ionization conditions were tested in positive electrospray mode and optimum fragmentation patterns were determined to optimize two selected reaction monitoring (SRM) transitions. Chromatographic conditions were optimized considering the chemical structure and chromatographic behavior of the analyzed compounds. The best performance was obtained with a Synergy Polar-RP column, which allowed the separation of the 38 compounds in 30 min. In addition, the performance of LC-MS/MS was studied in terms of linearity, sensitivity, intra- and inter-day precision, and overall robustness. The developed analytical method was able to quantify 27 of these neurochemicals in zebrafish chemical models for mild (P1), moderate (P2), and severe (P3) acute organophosphorus poisoning (OPP). The results show a general depression of synaptic-related neurochemicals, including the excitatory and inhibitory amino acids, as well as altered phospholipid metabolism, with specific neurochemical profiles associated to the different grades of severity. These results confirmed that the developed analytical method is a new tool for neurotoxicology research using the zebrafish model. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature. ; The research leading to these results has received funding from the European Research Council under European Union's Seven Framework Programme (FP/2007e2013)/ERC Grant Agreement n.320737, the NATO SfP project MD.SFPP 984777, and the grant CTM 2014-51985 from the Spanish Ministry of Economy, Industry and Competitiveness. Moreover, Rita Bausano is acknowledged for extraction samples support during her Erasmus Traineeship stage in the Environmental Chemistry Department at IDEA-CSIC (Barcelona, Spain). ; Peer reviewed

While the knowledge of plant metabolomes has increased in the last few years, their response to the presence of toxicants is still poorly understood. Here, we analyse the metabolomic changes in Japanese rice (Oryza sativa var. Japonica) upon exposure to heavy metals (Cd(ii) and Cu(ii)) in concentrations from 10 to 1000 μM. After harvesting, rice metabolites were extracted from aerial parts of the plants and analysed by HPLC (HILIC TSK gel amide-80 column) coupled to a mass spectrometer quadrupole-Orbitrap (Q-Exactive). Full scan and all ion fragmentation (AIF) mass spectrometry modes were used during the analysis. The proposed untargeted metabolomics data analysis strategy is based on the application of the multivariate curve resolution alternating least squares (MCR-ALS) method for feature detection, allowing the simultaneous resolution of pure chromatographic profiles and mass spectra of all metabolites present in the analysed rice extracts. All-ion fragmentation data were used to confirm the identification of MCR-ALS resolved metabolites. A total of 112 metabolites were detected, and 97 of them were subsequently identified and confirmed. Pathway analysis of the observed metabolic changes suggested an underlying similarity of the responses of the plant to Cd(ii) and Cu(ii), although the former treatment appeared to be the more severe of the two. In both cases, secondary metabolism and amino acid-, purine-, carbon- and glycerolipid-metabolism pathways were affected, in a pattern consistent with reduction in plant growth and/or photosynthetic capacity and with induction of defence mechanisms to reduce cell damage. © The Royal Society of Chemistry 2017. ; The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 320737. The authors would like to thank Center for Research in Agricultural Genomics (CRAG) for kindly supplying Japanese rice seeds. ; Peer reviewed

In this work, two knowledge integration strategies based on multivariate curve resolution alternating least squares (MCR-ALS) were used for the simultaneous analysis of data from two metabolomic platforms. The benefits and the suitability of these integration strategies were demonstrated in a comparative study of the metabolite profiles from yeast (Saccharomyces cerevisiae) samples grown in non-fermentable (acetate) and fermentable (glucose) carbon source. Untargeted metabolomics data acquired by capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS) were jointly analysed. On the one hand, features obtained by independent MCR-ALS analysis of each dataset were joined to obtain a biological interpretation based on the combined metabolic network visualization. On the other hand, taking advantage of the common spectral mode, a low-level data fusion strategy was proposed merging CE-MS and LC-MS data before the MCR-ALS analysis to extract the most relevant features for further biological interpretation. Then, results obtained by the two presented methods were compared. Overall, the study highlights the ability of MCR-ALS to be used in any of both knowledge integration strategies for untargeted metabolomics. Furthermore, enhanced metabolite identification and differential carbon source response detection were achieved when considering a combination of LC-MS and CE-MS based platforms. © 2017 Elsevier B.V. ; This research has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. 320737. Some part of this study was also supported by a grant from the Spanish Ministry of Economy and Competitiveness (CTQ2014-56777-R and CTQ2015-66254). Also, recognition from the Catalan government (grant 2014 SGR 1106) is acknowledged. ; Peer reviewed

AbstractAlthough microbial degradation is a key sink of polycyclic aromatic hydrocarbons (PAH) in surface seawaters, there is a dearth of field-based evidences of regional divergences in biodegradation and the effects of PAHs on site-specific microbial communities. We compared the magnitude of PAH degradation and its impacts in short-term incubations of coastal Mediterranean and the Maritime Antarctica microbiomes with environmentally relevant concentrations of PAHs. Mediterranean bacteria readily degraded the less hydrophobic PAHs, with rates averaging 4.72 ± 0.5 ng L h−1. Metatranscriptomic responses showed significant enrichments of genes associated to horizontal gene transfer, stress response, and PAH degradation, mainly harbored by Alphaproteobacteria. Community composition changed and increased relative abundances of Bacteroidota and Flavobacteriales. In Antarctic waters, there was no degradation of PAH, and minimal metatranscriptome responses were observed. These results provide evidence for factors such as geographic region, community composition, and pre-exposure history to predict PAH biodegradation in seawater.

Changes on an organism by the exposure to environmental stressors may be characterized by hyperspectral images (HSI), which preserve the morphology of biological samples, and suitable chemometric tools. The approach proposed allows assessing and interpreting the effect of contaminant exposure on heterogeneous biological samples monitored by HSI at specific tissue levels. In this work, the model example used consists of the study of the effect of the exposure of chlorpyrifos-oxon on zebrafish tissues. To assess this effect, unmixing of the biological sample images followed by tissue-specific classification models based on the unmixed spectral signatures is proposed. Unmixing and classification are performed by multivariate curve resolution-alternating least squares (MCR-ALS) and partial least squares-discriminant analysis (PLS-DA), respectively. Crucial aspects of the approach are: (1) the simultaneous MCR-ALS analysis of all images from 1 population to take into account biological variability and provide reliable tissue spectral signatures, and (2) the use of resolved spectral signatures from control and exposed populations obtained from resampling of pixel subsets analyzed by MCR-ALS multiset analysis as information for the tissue-specific PLS-DA classification models. Classification results diagnose the presence of a significant effect and identify the spectral regions at a tissue level responsible for the biological change. ; The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 32073 (CHEMAGEB project). The authors of this work belong to the network of recognized research groups by the Catalan government (2014 SGR 1106) and acknowledge the support of the Spanish government through project CTQ2015-66254-C2-2-P. ICFO would like to acknowledge financial support from Laserlab-Europe (EU-H2020 654148), the Spanish MINECO (Severo Ochoa grant SEV-2015-0522), Marató de TV3 (20142030), and the National Institute of Health (NIH, grant 5R21CA187890-02). The research conducted at ICFO's Super Resolution Light Microscopy and Nanoscopy Facility has been partially supported by Fundació Cellex Barcelona. ; Peer reviewed

Inhibition and aging of neuropathy target esterase (NTE) by exposure to neuropathic organophosphorus compounds (OPs) can result in OP-induced delayed neuropathy (OPIDN). In the present study we aimed to build a model of OPIDN in adult zebrafish. First, inhibition and aging of zebrafish NTE activity were characterized in the brain by using the prototypic neuropathic compounds cresyl saligenin phosphate (CBDP) and diisopropylphosphorofluoridate (DFP). Our results show that, as in other animal models, zebrafish NTE is inhibited and aged by both neuropathic OPs. Then, a neuropathic concentration inhibiting NTE activity by at least 70% for at least 24 h was selected for each compound to analyze changes in phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs) and glycerolphosphocholine (GPC) profiles. In spite to the strong inhibition of the NTE activity found for both compounds, only a mild increase in the LPCs level was found after 48 h of the exposure to DFP, and no effect were observed by CBDP. Moreover, histopathological evaluation and motor function outcome analyses failed to find any neurological abnormalities in the exposed fish. Thus, our results strongly suggest that zebrafish is not a suitable species for the development of an experimental model of human OPIDN. © 2018 The Author(s). ; This study was funded by the NATO SfP project MD.SFPP 984777 (D.R.), the European Research Council under European Union's Seven Framework Programme (FP/2007–2013)/ERC Grant Agreement n. 320737, and the Spanish Government (CTM2017-83242-R; D.R.). M.F. acknowledges the financial support from the Government of Catalonia through a Beatriu de Pinos fellowship (2016 BP-B 00233). I.F. was supported by the Ministry of Economy and Competitivity of Spain (FPI grant BES-2015-075023). The authors thank Mr. Marc Mañas for his valuable assistance building the Open Field Test setup. ; Peer reviewed