High-resolution mass spectrometry identifies delayed biomarkers for improved precision in acetaminophen/paracetamol human biomonitoring.

Paracetamol/acetaminophen (N-acetyl-p-aminophenol, APAP) is a top selling analgesic used in more than 600 prescription and non-prescription pharmaceuticals. To study efficiently some of the potential undesirable effects associated with increasing APAP consumption (e.g., developmental disorders, drug-induced liver injury), there is a need to improve current APAP biomonitoring methods that are limited by APAP short half-life. Here, we demonstrate using high-resolution mass spectrometry (HRMS) in several human studies that APAP thiomethyl metabolite conjugates (S-methyl-3-thioacetaminophen sulfate and S-methyl-3-thioacetaminophen sulphoxide sulfate) are stable biomarkers with delayed excretion rates compared to conventional APAP metabolites, that could provide a more reliable history of APAP ingestion in epidemiological studies. We also show that these biomarkers could serve as relevant clinical markers to diagnose APAP acute intoxication in overdosed patients, when free APAP have nearly disappeared from blood. Using in vitro liver models (HepaRG cells and primary human hepatocytes), we then confirm that these thiomethyl metabolites are directly linked to the toxic N-acetyl-p-benzoquinone imine (NAPQI) elimination, and produced via an overlooked pathway called the thiomethyl shunt pathway. Further studies will be needed to determine whether the production of the reactive hepatotoxic NAPQI metabolites is currently underestimated in human. Nevertheless, these biomarkers could already serve to improve APAP human biomonitoring, and investigate, for instance, inter-individual variability in NAPQI production to study underlying causes involved in APAP-induced hepatotoxicity. Overall, our findings demonstrate the potential of exposomics-based HRMS approach to advance towards a better precision for human biomonitoring.

Temporal air quality (NO2, O3, and PM10) changes in urban and rural stations in Catalonia during COVID-19 lockdown: an association with human mobility and satellite data.

In this study, changes in air quality by NO2, O3, and PM10 in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d'Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO2 lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, - 63% and Begur, - 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO2, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O3 levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NOx. PM10 lockdown levels decreased, mostly in Gràcia, Vall d'Hebron, and Granollers (- 35, - 39%, and - 39%, respectively) due to traffic depletion (- 90% in Barcelona's transport). Correlation among mobility index in Barcelona (- 100% in retail and recreation) and contamination was positive for NO2 and PM10 and negative for O3 (P < 0.001). Satellite images evidenced two hotspots of NO2 in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO2, O3 and PM10 levels below WHOAQG values in most of stations opposed to the excess registered in previous years.

ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets.

BACKGROUND: The analysis of LC-MS metabolomic datasets appears to be a challenging task in a wide range of disciplines since it demands the highly extensive processing of a vast amount of data. Different LC-MS data analysis packages have been developed in the last few years to facilitate this analysis. However, most of these strategies involve chromatographic alignment and peak shaping and often associate each "feature" (i.e., chromatographic peak) with a unique m/z measurement. Thus, the development of an alternative data analysis strategy that is applicable to most types of MS datasets and properly addresses these issues is still a challenge in the metabolomics field. RESULTS: Here, we present an alternative approach called ROIMCR to: i) filter and compress massive LC-MS datasets while transforming their original structure into a data matrix of features without losing relevant information through the search of regions of interest (ROIs) in the m/z domain and ii) resolve compressed data to identify their contributing pure components without previous alignment or peak shaping by applying a Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) analysis. In this study, the basics of the ROIMCR method are presented in detail and a detailed description of its implementation is also provided. Data were analyzed using the MATLAB (The MathWorks, Inc., www.mathworks.com ) programming and computing environment. The application of the ROIMCR methodology is described in detail, with an example of LC-MS data generated in a lipidomic study and with other examples of recent applications. CONCLUSIONS: The methodology presented here combines the benefits of data filtering and compression based on the searching of ROI features, without the loss of spectral accuracy. The method has the benefits of the application of the powerful MCR-ALS data resolution method without the necessity of performing chromatographic peak alignment or modelling. The presented method is a powerful alternative to other existing data analysis approaches that do not use the MCR-ALS method to resolve LC-MS data. The ROIMCR method also represents an improved strategy compared to the direct applications of the MCR-ALS method that use less-powerful data compression strategies such as binning and windowing. Overall, the strategy presented here confirms the usefulness of the ROIMCR chemometrics method for analyzing LC-MS untargeted metabolomics data.

Diet-sourced carbon-based nanoparticles induce lipid alterations in tissues of zebrafish (Danio rerio) with genomic hypermethylation changes in brain.

With rising environmental levels of carbon-based nanoparticles (CBNs), there is an urgent need to develop an understanding of their biological effects in order to generate appropriate risk assessment strategies. Herein, we exposed zebrafish via their diet to one of four different CBNs: C60 fullerene (C60), single-walled carbon nanotubes (SWCNT), short multi-walled carbon nanotubes (MWCNTs) or long MWCNTs. Lipid alterations in male and female zebrafish were explored post-exposure in three target tissues (brain, gonads and gastrointestinal tract) using 'omic' procedures based in liquid chromatography coupled with mass spectrometry (LC-MS) data files. These tissues were chosen as they are often target tissues following environmental exposure. Marked alterations in lipid species are noted in all three tissues. To further explore CBN-induced brain alterations, Raman microspectroscopy analysis of lipid extracts was conducted. Marked lipid alterations are observed with males responding differently to females; in addition, there also appears to be consistent elevations in global genomic methylation. This latter observation is most profound in female zebrafish brain tissues post-exposure to short MWCNTs or SWCNTs (P < 0.05). This study demonstrates that even at low levels, CBNs are capable of inducing significant cellular and genomic modifications in a range of tissues. Such alterations could result in modified susceptibility to other influences such as environmental exposures, pathology and, in the case of brain, developmental alterations.

Perfluoroalkylated Substance Effects in Xenopus laevis A6 Kidney Epithelial Cells Determined by ATR-FTIR Spectroscopy and Chemometric Analysis.

The effects of four perfluoroalkylated substances (PFASs), namely, perfluorobutanesulfonate (PFBS), perfluorooctanoic acid (PFOA), perfluorooctanesulfonate (PFOS), and perfluorononanoic acid (PFNA) were assessed in Xenopus laevis A6 kidney epithelial cells by attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometric analysis. Principal component analysis-linear discriminant analysis (PCA-LDA) was used to visualize wavenumber-related alterations and ANOVA-simultaneous component analysis (ASCA) allowed data processing considering the underlying experimental design. Both analyses evidenced a higher impact of low-dose PFAS-treatments (10(-9) M) on A6 cells forming monolayers, while there was a larger influence of high-dose PFAS-treatments (10(-5) M) on A6 cells differentiated into dome structures. The observed dose-response PFAS-induced effects were to some extent related to their cytotoxicity: the EC50-values of most influential PFAS-treatments increased (PFOS < PFNA < PFOA ≪ PFBS), and higher-doses of these chemicals induced a larger impact. Major spectral alterations were mainly attributed to DNA/RNA, secondary protein structure, lipids, and fatty acids. Finally, PFOS and PFOA caused a decrease in A6 cell numbers compared to controls, whereas PFBS and PFNA did not significantly change cell population levels. Overall, this work highlights the ability of PFASs to alter A6 cells, whether forming monolayers or differentiated into dome structures, and the potential of PFOS and PFOA to induce cell death.

Chemometric strategy for untargeted lipidomics: biomarker detection and identification in stressed human placental cells.

A lipidomic study was developed in a human placental choriocarcinoma cell line (JEG-3) exposed to tributyltin (TBT) and to a mixture of perfluorinated chemicals (PFCs). The method was based on the application of multivariate curve resolution-alternating least squares (MCR-ALS) to data sets obtained by ultra-high performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC-TOF-MS) using an untargeted approach. Lipids from exposed JEG-3 cells were solid-liquid extracted and analyzed by UHPLC-TOF-MS in full scan mode, together with control samples. Raw UHPLC-TOF-MS data of the different cell samples were subdivided into 20 distinct chromatographic windows and each window was further organized in a column-wise augmented data matrix, where data from every sample was in an individual data matrix. Then, the 20 new augmented data matrices were modeled by MCR-ALS. A total number of 86 components were resolved and a statistical comparative study of their elution profiles showed distinct responses for the lipids of exposed versus control cells, evidencing a lipidome disruption attributed to the presence of the xenobiotics. Results from one-way ANOVA followed by a multiple comparisons test and from discriminant partial least squares (PLS-DA) analysis were compared as usual strategies for the determination of potential biomarkers. Identification of 24 out of the 33 proposed biomarkers contributed to the better understanding of the effects of PFCs and TBT in the lipidome of human placental cells. Overall, this study proposes an innovative untargeted LC-MS MCR-ALS approach valid for -omic sciences such as lipidomics.

Characterization of complex lipid mixtures in contaminant exposed JEG-3 cells using liquid chromatography and high-resolution mass spectrometry.

The aim of this study was to develop a method based on ultra high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS) for lipid profiling in human placental choriocarcinoma (JEG-3) cells. Lipids were solid-liquid extracted from JEG-3 cells using a solution of chloroform/methanol (2:1, v/v) in a simple procedure requiring minimal sample alteration. Simultaneous separation of complex lipid mixtures in their major classes was achieved with a reversed-phase (C8) UHPLC column and a mobile phase containing methanol with 1 mM ammonium formate and 0.2 % formic acid (A)/water with 2 mM ammonium formate and 0.2 % formic acid (B). Lipids were characterized using time-of-flight (TOF) and Orbitrap under full scan and positive electrospray ionization mode with both analyzers. A total of 178 species of lipids, including 37 phosphatidylcholines (PC), 32 plasmalogen PC, 9 lyso PC, 4 lyso plasmalogen PC, 30 triacylglycerols, 22 diacylglycerols, 7 cholesterol esters, 25 phosphatidylethanolamines, and 12 sphingomyelins, were identified using TOF and Orbitrap. The identification of all lipid classes was based on exact mass characterization with an error < 5 ppm. The developed methodology was applied to study lipid alterations in human placental cells against the exposure to perfluorinated chemicals (PFCs) and tributyltin (TBT).

Perfluorinated chemicals: differential toxicity, inhibition of aromatase activity and alteration of cellular lipids in human placental cells.

The cytotoxicity of eight perfluorinated chemicals (PFCs), namely, perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorododecanoic acid (PFDoA), perfluorobutanesulfonate (PFBS), perfluorohexanesulfonate (PFHxS) and perfluorooctanesulfonate (PFOS) was assessed in the human placental choriocarcinoma cell line JEG-3. Only the long chain PFCs--PFOS, PFDoA, PFNA, PFOA--showed significant cytotoxicity in JEG-3 cells with EC50 values in the range of 107 to 647 µM. The observed cytotoxicity was to some extent related to a higher uptake of the longer chain PFCs by cells (PFDoA>PFOS≫PFNA>PFOA>PFHxA). Moreover, this work evidences a high potential of PFOS, PFOA and PFBS to act as aromatase inhibitors in placental cells with IC50s in the range of 57-80 µM, the inhibitory effect of PFBS being particularly important despite the rather low uptake of the compound by cells. Finally, exposure of JEG-3 cells to a mixture of the eight PFCs (0.6 µM each) led to a relative increase (up to 3.4-fold) of several lipid classes, including phosphatidylcholines (PCs), plasmalogen PC and lyso plasmalogen PC, which suggests an interference of PFCs with membrane lipids. Overall, this work highlights the ability of the PFC mixture to alter cellular lipid pattern at concentrations well below those that generate toxicity, and the potential of the short chain PFBS, often considered a safe substitute of PFOS, to significantly inhibit aromatase activity in placental cells.