Metabolomic and sphingolipidomic profiling of human hepatoma cells exposed to widely used pharmaceuticals.

Pharmaceutical compounds have become one of the main contaminants of emerging concern (CECs) due to their high usage and increased release into the environment. This study aims to assess the effects caused by three widely consumed hepatotoxic pharmaceutical compounds: an antibiotic (amoxicillin), an antiepileptic (carbamazepine), and an antidepressant (trazodone), on human health when indirectly exposed to toxicologically relevant concentrations (30, 15, and 7.5 μM for amoxicillin and carbamazepine, and 4, 2, and 1 μM for trazodone).

Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms.

In recent years, instrumental improvements have enabled the spread of mass spectrometry-based lipidomics platforms in biomedical research. In mass spectrometry, the reliability of generated data varies for each compound, contingent on, among other factors, the availability of labeled internal standards. It is challenging to evaluate the data for lipids without specific labeled internal standards, especially when dozens to hundreds of lipids are measured simultaneously.

Effects of Indoor Dust Exposure on Lung Cells: Association of Chemical Composition with Phenotypic and Lipid Changes in a 3D Lung Cancer Cell Model.

Indoor dust is a key contributor to the global human exposome in urban areas since the population develops most of its activities in private and public buildings. To gain insight into the health risks associated with this chronic exposure, it is necessary to characterize the chemical composition of dust and understand its biological impacts using reliable physiological models. The present study investigated the biological effects of chemically characterized indoor dust extracts using three-dimensional (3D) lung cancer cell cultures combining phenotypic and lipidomic analyses.

Quantification strategies for two-dimensional liquid chromatography datasets using regions of interest and multivariate curve resolution approaches.

In this work, three chemometrics-based approaches are compared for quantification purposes when using two-dimensional liquid chromatography (LC×LC-MS), taking as a study case the quantification of amino acids in commercial drug mixtures. Although the approaches have been already used for one-dimensional gas or liquid chromatography, the main novelty of this work is the demonstration of their applicability to LC×LC-MS datasets. Besides, steps such as peak alignment and modelling, commonly applied in this type of data analysis, are not required with the approaches proposed here.

Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies.

The use of chemometric methods based on the analysis of variances (ANOVA) allows evaluation of the statistical significance of the experimental factors used in a study. However, classical multivariate ANOVA (MANOVA) has a number of requirements that make it impractical for dealing with metabolomics data. For this reason, in recent years, different options have appeared that overcome these limitations.

Lipidomic analysis of single and combined effects of polyethylene microplastics and polychlorinated biphenyls on human hepatoma cells.

Microplastics are an emerging environmental issue as a result of their ubiquity, persistence, and intrinsic toxic potential. In addition, their ability to sorb and transport a wide variety of environmental pollutants (i.e.

Interaction of Environmental Pollutants with Microplastics: A Critical Review of Sorption Factors, Bioaccumulation and Ecotoxicological Effects.

Microplastics have become one of the leading environmental threats due to their persistence, ubiquity and intrinsic toxic potential. The potential harm that microplastics impose on ecosystems varies from direct effects (i.e.

Partial characterization of the lipidome of the cold-water scallop, Chlamys islandica.

Fingerprinting of the main lipid components of the digestive gland of the Icelandic scallop-Chlamys islandica-has been performed by ultra-high-performance liquid chromatography coupled with time of flight high-resolution mass spectrometry, UHPLC-HRMS/ToF. This method allowed the identification of 224 lipids, including phosphatidylcholines (PC), plasmanyl (PC-O)/plasmenyl (PC-P) phosphatidylcholines, lyso-phosphatidylcholines (LPC), and their plasmanyl/plasmenyl forms (LPC-O/LPC-P). Diacylglycerols (DG), triacylglycerols (TG), and cholesteryl esters (CE) were the neutral lipids (NL) analyzed.

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.

Untargeted lipidomic evaluation of hydric and heat stresses on rice growth.

Environmental stresses are the major factors that limit the geographical distribution of plants. As a consequence, plants have developed different strategies to adapt to these environmental changes among which can be outlined the maintenance of membranes' integrity and fluidity. Lipids are key molecules for this environmental adaptation and a comprehensive understand of the molecular mechanisms underlying is still required.

Identification of antihypertensive peptides in nutraceuticals by capillary electrophoresis-mass spectrometry.

We present capillary electrophoresis-mass spectrometry (CE-MS) in combination with advanced chemometric tools for the analysis of bioactive compounds in food, in particular for the identification of antihypertensive peptides in a nutraceutical derived from a bovine milk protein hydrolysate. Different extracts of the nutraceutical were analyzed by CE-MS, and the electropherograms were processed using a novel data analysis workflow that included regions of interest (ROIs) compression and multivariate curve resolution alternating least squares (MCR-ALS). MCR-ALS permitted the description of the nutraceutical extract as ten characteristic components with their electrophoretic profiles and mass spectra.

An untargeted lipidomic strategy combining comprehensive two-dimensional liquid chromatography and chemometric analysis.

Untargeted lipidomic samples are extremely complex and often exceed the limits of peak capacity achievable by one-dimensional liquid chromatography (LC). Comprehensive two-dimensional liquid chromatography (LC × LC) appears as a promising alternative to overcome this drawback. Unfortunately, this approach generates highly complex datasets which untargeted analysis is challenging.

Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis.

Bisphenol A (BPA), perfluorooctane sulfonate (PFOS), and tributyltin (TBT) are emerging endocrine disruptors (EDCs) with still poorly defined mechanisms of toxicity and metabolic effects in aquatic organisms. We used an untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) metabolomic approach to study the effects of sub-lethal doses of these three EDCs on the metabolic profiles of zebrafish embryos exposed from 48 to 120hpf (hours post fertilization). Advanced chemometric data analysis methods were used to reveal effects on the subjacent regulatory pathways.

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC.

A chemometric approach for characterization of serum transthyretin in familial amyloidotic polyneuropathy type I (FAP-I) by electrospray ionization-ion mobility mass spectrometry.

In this study, we describe a chemometric data analysis approach to assist in the interpretation of the complex datasets from the analysis of high-molecular mass oligomeric proteins by ion mobility mass spectrometry (IM-MS). The homotetrameric protein transthyretin (TTR) is involved in familial amyloidotic polyneuropathy type I (FAP-I). FAP-I is associated with a specific TTR mutant variant (TTR(Met30)) that can be easily detected analyzing the monomeric forms of the mutant protein.

Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches.

Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward.

Analysis of multiple mass spectrometry images from different Phaseolus vulgaris samples by multivariate curve resolution.

A new procedure based on the simultaneous analysis of multiple mass spectrometry images using multivariate curve resolution is presented in this work. Advantages of the application of the proposed approach are shown for three cases of plant studies demonstrating its potential usefulness in metabolomics studies, particularly in lipidomics. In the first dataset, a three stage germination time course process of green bean seeds is presented.

Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach.

Although bisphenol A (BPA) is commonly recognized as an endocrine disruptor, the metabolic consequences of its exposure are still poorly understood. In this study, we present a non-targeted LC-MS based metabolomic analysis in combination with a full-genome, high-throughput RNA sequencing (RNA-Seq) to reveal the metabolic effects and the subjacent regulatory pathways of exposing zebrafish embryos to BPA during the first 120 hours post-fertilization. We applied multivariate data analysis methods to extract biochemical information from the LC-MS and RNA-Seq complex datasets and to perform testable predictions of the phenotypic adverse effects.

Untargeted Comprehensive Two-Dimensional Liquid Chromatography Coupled with High-Resolution Mass Spectrometry Analysis of Rice Metabolome Using Multivariate Curve Resolution.

In this work, a new strategy for the chemometric analysis of two-dimensional liquid chromatography-high-resolution mass spectrometry (LC × LC-HRMS) data is proposed. This approach consists of a preliminary compression step along the mass spectrometry (MS) spectral dimension based on the selection of the regions of interest (ROI), followed by a further data compression along the chromatographic dimension by wavelet transforms. In a secondary step, the multivariate curve resolution alternating least squares (MCR-ALS) method is applied to previously compressed data sets obtained in the simultaneous analysis of multiple LC × LC-HRMS chromatographic runs from multiple samples.

Knowledge integration strategies for untargeted metabolomics based on MCR-ALS analysis of CE-MS and LC-MS data.

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.

Metabolomic analysis of the effects of cadmium and copper treatment in Oryza sativa L. using untargeted liquid chromatography coupled to high resolution mass spectrometry and all-ion fragmentation.

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.

The human mitochondrial transcription factor A is a versatile G-quadruplex binding protein.

The ability of the guanine-rich strand of the human mitochondrial DNA (mtDNA) to form G-quadruplex structures (G4s) has been recently highlighted, suggesting potential functions in mtDNA replication initiation and mtDNA stability. G4 structures in mtDNA raise the question of their recognition by factors associated with the mitochondrial nucleoid. The mitochondrial transcription factor A (TFAM), a high-mobility group (HMG)-box protein, is the major binding protein of human mtDNA and plays a critical role in its expression and maintenance.

Chemometric analysis of comprehensive LC×LC-MS data: Resolution of triacylglycerol structural isomers in corn oil.

Comprehensive hyphenated two-dimensional liquid chromatography mass spectrometry (LC×LC-MS) is a very powerful analytical tool achieving high throughput resolution of highly complex natural samples. However, even using this approach there is still the possibility of not resolving some of the analytes of interest. For instance, triacylglycerols (TAGs) structural isomers in oil samples are extremely difficult to separate chromatographically due to their very similar structure and chemical properties.