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

Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion

Data-independent acquisition-all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.

Recent advances in medicinal and edible homologous plant polysaccharides: Preparation, structure and prevention and treatment of diabetes

Medicinal and edible homologs (MEHs) can be used in medicine and food. The National Health Commission announced that a total of 103 kinds of medicinal and edible homologous plants (MEHPs) would be available by were available in 2023. Diabetes mellitus (DM) has become the third most common chronic metabolic disease that seriously threatens human health worldwide. Polysaccharides, the main component isolated from MEHPs, have significant antidiabetic effects with few side effects. Based on a literature search, this paper summarizes the preparation methods, structural characterization, and antidiabetic functions and mechanisms of MEHPs polysaccharides (MEHPPs). Specifically, MEHPPs mainly regulate PI3K/Akt, AMPK, cAMP/PKA, Nrf2/Keap1, NF-κB, MAPK and other signaling pathways to promote insulin secretion and release, improve glycolipid metabolism, inhibit the inflammatory response, decrease oxidative stress and regulate intestinal flora. Among them, 16 kinds of MEHPPs were found to have obvious anti-diabetic effects. This article reviews the prevention and treatment of diabetes and its complications by MEHPPs and provides a basis for the development of safe and effective MEHPP-derived health products and new drugs to prevent and treat diabetes.

Rapid and Highly Efficient Separation of i-Motif DNA Species by CE-UV and Multivariate Curve Resolution

The i-motif is a class of nonstandard DNA structure with potential biological implications. A novel capillary electrophoresis with an ultraviolet absorption spectrophotometric detection (CE-UV) method has been developed for the rapid analysis of the i-motif folding equilibrium as a function of pH and temperature. The electrophoretic analyses are performed in reverse polarity of the separation voltage with 32 cm long fused silica capillaries permanently coated with hydroxypropyl cellulose (HPC), after an appropriate conditioning procedure was used to achieve good repeatability. However, the electrophoretic separation between the folded and unfolded conformers of the studied cytosine-rich i-motif sequences (i.e., TT, Py39WT, and nmy01) is compromised, especially for Py39WT and nmy01, which result in completely overlapped peaks. Therefore, deconvolution with multivariate curve resolution-alternating least-squares (MCR-ALS) has been required for the efficient separation of the folded and unfolded species found at different concentration levels at pH 6.5 and between 12 and 40 °C, taking advantage of the small dissimilarities in the electrophoretic mobilities and UV spectra levels. MCR-ALS has also provided quantitative information that has been used to estimate melting temperatures (Tm), which are similar to those determined by UV and circular dichroism (CD) spectroscopies. The obtained results demonstrate that CE-UV assisted by MCR-ALS may become a very useful tool to get novel insight into the folding of i-motifs and other complex DNA structures.

Linking MS1 and MS2 signals in positive and negative modes of LC-HRMS in untargeted metabolomics using the ROIMCR approach

Data-independent acquisition (DIA) mode in liquid chromatography (LC) high-resolution mass spectrometry (HRMS) has emerged as a powerful strategy in untargeted metabolomics for detecting a broad range of metabolites. However, the use of this approach also represents a challenge in the analysis of the large datasets generated. The regions of interest (ROI) multivariate curve resolution (MCR) approach can help in the identification and characterization of unknown metabolites in their mixtures by linking their MS1 and MS2 DIA spectral signals. In this study, it is proposed for the first time the analysis of MS1 and MS2 DIA signals in positive and negative electrospray ionization modes simultaneously to increase the coverage of possible metabolites present in biological systems. In this work, this approach has been tested for the detection and identification of the amino acids present in a standard mixture solution and in fish embryo samples. The ROIMCR analysis allowed for the identification of all amino acids present in the analyzed mixtures in both positive and negative modes. The methodology allowed for the direct linking and correspondence between the MS signals in their different acquisition modes. Overall, this approach confirmed the advantages and possibilities of performing the proposed ROIMCR simultaneous analysis of mass spectrometry signals in their differing acquisition modes in untargeted metabolomics studies.

Augmented region of interest for untargeted metabolomics mass spectrometry (AriumMS) of multi-platform-based CE-MS and LC-MS data

In mass spectrometry (MS)-based metabolomics, there is a great need to combine different analytical separation techniques to cover metabolites of different polarities and apply appropriate multi-platform data processing. Here, we introduce AriumMS (augmented region of interest for untargeted metabolomics mass spectrometry) as a reliable toolbox for multi-platform metabolomics. AriumMS offers augmented data analysis of several separation techniques utilizing a region-of-interest algorithm. To demonstrate the capabilities of AriumMS, five datasets were combined. This includes three newly developed capillary electrophoresis (CE)-Orbitrap MS methods using the recently introduced nanoCEasy CE-MS interface and two hydrophilic interaction liquid chromatography (HILIC)-Orbitrap MS methods. AriumMS provides a novel mid-level data fusion approach for multi-platform data analysis to simplify and speed up multi-platform data processing and evaluation. The key feature of AriumMS lies in the optimized data processing strategy, including parallel processing of datasets and flexible parameterization for processing of individual separation methods with different peak characteristics. As a case study, Saccharomyces cerevisiae (yeast) was treated with a growth inhibitor, and AriumMS successfully differentiated the metabolome based on the augmented multi-platform CE-MS and HILIC-MS investigation. As a result, AriumMS is proposed as a powerful tool to improve the accuracy and selectivity of metabolome analysis through the integration of several HILIC-MS/CE-MS techniques.

Data Fusion Approach to Simultaneously Evaluate the Degradation Process Caused by Ozone and Humidity on Modern Paint Materials

The knowledge of the atmospheric degradation reactions affecting the stability of modern materials is still of current interest. In fact, environmental parameters, such as relative humidity (RH), temperature, and pollutant agents, often fluctuate due to natural or anthropogenic climatic changes. This study focuses on evaluating analytical and statistical strategies to investigate the degradation processes of acrylic and styrene-acrylic paints after exposure to ozone (O₃) and RH. A first comparison of FTIR and Py-GC/MS results allowed to obtain qualitative information on the degradation products and the influence of the pigments on the paints’ stability. The combination of these results represents a significant potential for the use of data fusion methods. Specifically, the datasets obtained by FTIR and Py-GC/MS were combined using a low-level data fusion approach and subsequently processed by principal component analysis (PCA). It allowed to evaluate the different chemical impact of the variables for the characterization of unaged and aged samples, understanding which paint is more prone to ozone degradation, and which aging variables most compromise their stability. The advantage of this method consists in simultaneously evaluating all the FTIR and Py-GC/MS variables and describing common degradation patterns. From these combined results, specific information was obtained for further suitable conservation practices for modern and contemporary painted films.

A Study on the Volatile Compounds in Elaeagnus angustifolia L. Flowers during Flowering Season by Gas Chromatography-Mass Spectrometry Coupled with Advanced Chemometrics

The flowers of Elaeagnus angustifolia L. have been used as a homologous variety in China, whose quality seriously relies on the compositions during the flowering period. Unfortunately, studies on the variations of volatile compounds during the flowering season are rarely reported. Herein, a gas chromatography-mass spectrometry-based untargeted metabolomic methodology was proposed for the comprehensive analysis of volatile compounds in E. angustifolia flowers to classify various flowering stages. Samples from four flowering stages were collected, including the initial bloom stage, pre-full bloom stage (70–80% of flowers), full bloom stage, and ending of the bloom stage. Simultaneous distillation extraction was used for the extraction of volatile compounds in the flowers, which was then analyzed by a newly developed chemometric data analysis tool, autoGCMSDataAnal. An advantage of the developed methodology is that compounds can be accurately screened and identified. Finally, 59 compounds that showed significant difference among four flowering stages were screened and 31 compounds were identified. Sample clustering results from principal component analysis and hierarchical clustering analysis suggested that flowers from the pre-full bloom stage and full bloom stage may be more suitable when used as raw materials for industrial products.

Untargeted metabolomics of prostate cancer zwitterionic and positively charged compounds in urine

Prostate cancer, a leading cause of cancer-related deaths worldwide, principally occurs in over 50-year-old men. Nowadays there is urgency to discover biomarkers alternative to prostate-specific antigen, as it cannot discriminate patients with benign prostatic hyperplasia from clinically significant forms of prostatic cancer. In the present paper, 32 benign prostatic hyperplasia and 41 prostatic cancer urine samples were collected and analyzed. Polar and positively charged metabolites were therein investigated using an analytical platform comprising an up to 40-fold analyte enrichment step by graphitized carbon black solid-phase extraction, HILIC separation, and untargeted high-resolution mass spectrometry analysis. These classes of compounds are often neglected in common metabolomics experiments even though previous studies reported their significance in cancer biomarker discovery. The complex metabolomics big datasets, generated by the UHPLC-HRMS, were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest data and their analysis by the Multivariate Curve-Resolution Alternating Least Squares chemometrics method. This approach allowed the resolution and tentative identification of the metabolites differentially expressed by the two data sets. Among these, amino acids and carnitine derivatives were tentatively identified highlighting the importance of the proposed methodology for cancer biomarker research.

Insights into chemical and sensorial aspects to understand and manage beer aging using chemometrics

Beer chemical instability remains, at present, the main challenge in maintaining beer quality. Although not fully understood, after decades of research, significant progress has been made in identifying "aging compounds," their origin, and formation pathways. However, as the nature of aging relies on beer manufacturing aspects such as raw materials, process variables, and storage conditions, the chemical profile differs among beers. Current research points to the impact of nonoxidative reactions on beer quality. The effect of Maillard and Maillard intermediates on the final beer quality has become the focus of beer aging research, as prevention of oxidation can only sustain beer quality to some extent. On the other hand, few studies have focused on tracing a profile of whose compound is sensory relevant to specific types of beer. In this matter, the incorporation of "chemometrics," a class of multivariate statistic procedures, has helped brewing scientists achieve specific correlations between the sensory profile and chemical data. The use of chemometrics as exploratory data analysis, discrimination techniques, and multivariate calibration techniques has made the qualitatively and quantitatively translation of sensory perception of aging into manageable chemical and analytical parameters. However, despite their vast potential, these techniques are rarely employed in beer aging studies. This review discusses the chemical and sensorial bases of beer aging. It focuses on how chemometrics can be used to their full potential, with future perspectives and research to be incorporated in the field, enabling a deeper and more specific understanding of the beer aging picture.

Evaluation of Nontarget Long-Term LC-HRMS Time Series Data Using Multivariate Statistical Approaches

The use of liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has steadily increased in many application fields ranging from metabolomics to environmental science. HRMS data are frequently used for nontarget screening (NTS), i.e., the search for compounds that are not previously known and where no reference substances are available. However, the large quantity of data produced by NTS analytical workflows makes data interpretation and time-dependent monitoring of samples very sophisticated and necessitates exploiting chemometric data processing techniques. Consequently, in this study, a prioritization method to handle time series in nontarget data was established. As proof of concept, industrial wastewater was investigated. As routine industrial wastewater analyses monitor the occurrence of a limited number of targeted water contaminants, NTS provides the opportunity to detect also unknown trace organic compounds (TrOCs) that are not in the focus of routine target analysis. The developed prioritization method enables reducing raw data and including identification of prioritized unknown contaminants. To that end, a five-month time series for industrial wastewaters was utilized, analyzed by liquid chromatography-time-of-flight mass spectrometry (LC-qTOF-MS), and evaluated by NTS. Following peak detection, alignment, grouping, and blank subtraction, 3303 features were obtained of wastewater treatment plant (WWTP) influent samples. Subsequently, two complementary ways for exploratory time trend detection and feature prioritization are proposed. Therefore, following a prefiltering step, featurewise principal component analysis (PCA) and groupwise PCA (GPCA) of the matrix (temporal wise) were used to annotate trends of relevant wastewater contaminants. With sparse factorization of data matrices using GPCA, groups of correlated features/mass fragments or adducts were detected, recovered, and prioritized. Similarities and differences in the chemical composition of wastewater samples were observed over time to reveal hidden factors accounting for the structure of the data. The detected features were reduced to 130 relevant time trends related to TrOCs for identification. Exemplarily, as proof of concept, one nontarget pollutant was identified as N-methylpyrrolidone. The developed chemometric strategies of this study are not only suitable for industrial wastewater but also could be efficiently employed for time trend exploration in other scientific fields.

CE-MS metabolic profiling of volume-restricted plasma samples from an acute mouse model for epileptic seizures to discover potentially involved metabolomic features

Currently, a high variety of analytical techniques to perform metabolomics is available. One of these techniques is capillary electrophoresis coupled to mass spectrometry (CE-MS), which has emerged as a rather strong analytical technique for profiling polar and charged compounds. This work aims to discover with CE-MS potential metabolic consequences of evoked seizures in plasma by using a 6Hz acute corneal seizure mouse model. CE-MS is an appealing technique because of its capability to handle very small sample volumes, such as the 10 μL plasma samples obtained using capillary microsampling in this study. After liquid-liquid extraction, the samples were analyzed with CE-MS using low-pH separation conditions, followed by data analysis and biomarker identification. Both electrically induced seizures showed decreased values of methionine, lysine, glycine, phenylalanine, citrulline, 3-methyladenine and histidine in mice plasma. However, a second provoked seizure, 13 days later, showed a less pronounced decrease of the mean concentrations of these plasma metabolites, demonstrated by higher fold change ratios. Other obtained markers that can be related to seizure activities based on literature data, are isoleucine, serine, proline, tryptophan, alanine, arginine, valine and asparagine. Most amino acids showed relatively stable plasma concentrations between the basal levels (Time point 1) and after the 13-day wash-out period (Time point 3), which suggests its effectiveness. Overall, this work clearly demonstrated the possibility of profiling metabolite consequences related to seizure activities of an intrinsically low amount of body fluid using CE-MS. It would be useful to investigate and validate, in the future, the known and unknown metabolites in different animal models as well as in humans.

GM2-GM3 gangliosides ratio is dependent on GRP94 through down-regulation of GM2-AP cofactor in brain metastasis cells

GRP94 is an ATP-dependent chaperone able to regulate pro-oncogenic signaling pathways. Previous studies have shown a critical role of GRP94 in brain metastasis (BrM) pathogenesis and progression. In this work, an untargeted lipidomic analysis revealed that some lipid species were altered in GRP94-deficient cells, specially GM2 and GM3 gangliosides. The catalytic pathway of GM2 is affected by the low enzymatic activity of β-Hexosaminidase (HexA), responsible for the hydrolysis of GM2 to GM3. Moreover, a deficiency of the GM2-activator protein (GM2-AP), the cofactor of HexA, is observed without alteration of gene expression, indicating a post-transcriptional alteration of GM2-AP in the GRP94-ablated cells. One plausible explanation of these observations is that GM2-AP is a client of GRP94, resulting in defective GM2 catabolic processing and lysosomal accumulation of GM2 in GRP94-ablated cells. Overall, given the role of gangliosides in cell surface dynamics and signaling, their imbalance might be linked to modifications of cell behaviour acquired in BrM progression. This work indicates that GM2-AP could be an important factor in ganglioside balance maintenance. These findings highlight the relevance of GM3 and GM2 gangliosides in BrM and reveal GM2-AP as a promising diagnosis and therapeutic target in BrM research.

Assessing the suitability of capillary electrophoresis-mass spectrometry for biomarker discovery in plasma-based metabolomics

The actual utility of capillary electrophoresis-mass spectrometry (CE-MS) for biomarker discovery using metabolomics still needs to be assessed. Therefore, a simulated comparative metabolic profiling study for biomarker discovery by CE-MS was performed, using pooled human plasma samples with spiked biomarkers. Two studies have been carried out in this work. Focus of study I was on comparing two sets of plasma samples, in which one set (class I) was spiked with five isotope-labeled compounds, whereas another set (class II) was spiked with six different isotope-labeled compounds. In study II, focus was also on comparing two sets of plasma samples, however, the isotope-labeled compounds were spiked to both class I and class II samples but with concentrations which differ by a factor two between both classes (with one compound absent in each class). The aim was to determine whether CEMS-based metabolomics could reveal the spiked biomarkers as the main classifiers, applying two different data analysis software tools (MetaboAnalyst and Matlab). Unsupervised analysis of the recorded metabolic profiles revealed a clear distinction between class I and class II plasma samples in both studies. This classification was mainly attributed to the spiked isotope-labeled compounds, thereby emphasizing the utility of CE-MS for biomarker discovery.

An initial estimation method using cosine similarity for multivariate curve resolution: application to NMR spectra of chemical mixtures

Mixture spectra is decomposed into pure spectra without prior knowledge, and the MCR calculation refines the spectra and provides the concentrations.

Wine and grape marc spirits metabolomics

INTRODUCTION

Mass spectrometry (MS)-based and nuclear magnetic resonance (NMR) spectroscopic analyses play a key role in the field of metabolomics due to their important advantages. The use of metabolomics in wine and grape marc spirits allows a more holistic perspective in monitoring and gaining information on the making processes and thus it can assist on the improvement of their quality.

OBJECTIVES

This review surveys the latest metabolomics approaches for wine and grape marc spirits with a focus on the description of MS-based and NMR spectroscopic analytical techniques.

METHODS

We reviewed the literature to identify metabolomic studies of wine and grape marc spirits that were published until the end of 2017, with the key term combinations of 'metabolomics', 'wine' and 'grape marc spirits'. Through the reference lists from these studies, additional articles were identified.

RESULTS

The results of this review showed that the application of different metabolomics approaches has significantly increased the knowledge of wine metabolome and grape marc spirits; however there is not yet a single analytical platform that can completely separate, detect and identify all metabolites in one analysis.

CONCLUSIONS

The authentication and quality control of wines and grape marc spirits has to be taken with caution, since the product's chemical composition could be affected by many factors. Despite intrinsic limitations, NMR spectroscopy and MS based strategies remain the key analytical methods in metabolomics studies. Authenticity, traceability and health issues related to their consumption are the major research initiatives in wine and grape marc spirits metabolomics analysis.

Dose-dependent transcriptomic responses of zebrafish eleutheroembryos to Bisphenol A

Despite the abundant literature on the adverse effects of Bisphenol A (BPA) as endocrine disruptor, its toxicity mechanisms are still poorly understood. We present here a study of its effects on the zebrafish eleutheroembryo transcriptome at concentrations ranging from 0.1 to 4 mg L^-1, this latter representing the lowest observed effect concentration (LOEC) found in our study at three different macroscopical endpoints (survival, hatching and swim bladder inflation). Multivariate data analysis methods identified both monotonic and bi-phasic patterns of dose-dependent responses. Functional analyses of genes affected by BPA exposure suggest an interaction of BPA with different signaling pathways, being the estrogenic and retinoid receptors two likely targets. In addition, we identified an apparently unrelated inhibitory effect on, among others, visual function genes. We interpret our data as the result of a sum of underlying, independent molecular mechanisms occurring simultaneously at the exposed animals, well below the macroscopic LOEC, but related to at least some of the observed morphological alterations, particularly in eye size and yolk sac resorption. Our data supports the idea that the physiological effects of BPA cannot be only explained by its rather weak interaction with the estrogen receptor, and that multivariate analyses are required to analyze the effects of toxicants like BPA, which interact with different cellular targets producing complex phenotypes.

Recent advances in capillary electrophoresis-mass spectrometry: Instrumentation, methodology and applications

Capillary electrophoresis (CE) offers fast and high-resolution separation of charged analytes from small injection volumes. Coupled to mass spectrometry (MS), it represents a powerful analytical technique providing (exact) mass information and enables molecular characterization based on fragmentation. Although hyphenation of CE and MS is not straightforward, much emphasis has been placed on enabling efficient ionization and user-friendly coupling. Though several interfaces are now commercially available, research on more efficient and robust interfacing with nano-electrospray ionization (ESI), matrix-assisted laser desorption/ionization (MALDI) and inductively coupled plasma mass spectrometry (ICP) continues with considerable results. At the same time, CE-MS has been used in many fields, predominantly for the analysis of proteins, peptides and metabolites. This review belongs to a series of regularly published articles, summarizing 248 articles covering the time between June 2016 and May 2018. Latest developments on hyphenation of CE with MS as well as instrumental developments such as two-dimensional separation systems with MS detection are mentioned. Furthermore, applications of various CE-modes including capillary zone electrophoresis (CZE), nonaqueous capillary electrophoresis (NACE), capillary gel electrophoresis (CGE) and capillary isoelectric focusing (CIEF) coupled to MS in biological, pharmaceutical and environmental research are summarized.

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. EDC treatments induced changes in concentrations of about 50 metabolites for TBT and BPA, and of 25 metabolites for PFOS. The analysis of the corresponding metabolic changes suggested the presence of similar underlying zebrafish responses to BPA, TBT and PFOS affecting the metabolism of glycerophospholipids, amino acids, purines and 2-oxocarboxylic acids. We related the changes in glycerophospholipid metabolism to alterations in absorption of the yolk sack, the main source of nutrients (including lipids) for the developing embryo, linking the molecular markers with adverse phenotypic effects. We propose a general mode of action for all three chemical compounds, probably related to their already described interaction with the PPAR/RXR complex, combined with specific effects on different signaling pathways resulting in particular alterations in the zebrafish embryos metabolism.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

Phenotypic and lipidomic characterization of primary human epidermal keratinocytes exposed to simulated solar UV radiation

BACKGROUND

Ultraviolet (UV) radiation is known to be one of the most important environmental hazards acting on the skin. The most part of UV radiation is absorbed in the epidermis, where keratinocytes are the most abundant and exposed cell type. Lipids have an important role in skin biology, not only for their important contribution to the maintenance of the permeability barrier but also for the production and storage of energy, membrane organization and cell signalling functions. However, the effects on the lipid composition of keratinocytes under UV radiation are little explored.

OBJECTIVE

The present work aims to explore the effects on the phenotype and lipid content of primary human keratinocytes exposed to simulated solar UV radiation.

METHODS

Keratinocytes were exposed to a single (acute exposure) and repeated simulated solar UV irradiations for 4 weeks (chronic exposure). Cell viability and morphology were explored, as well as the production of reactive oxygen species. Then, lipid extracts were analysed through liquid chromatography coupled to mass spectrometry (LC-MS) and the data generated was processed using the ROIMCR chemometric methodology together with partial least squares discriminant analysis (PLS-DA), to finally reveal the most relevant lipid changes that occurred in keratinocytes upon UV irradiation. Also, the potential induction of keratinocyte differentiation was explored by measuring the increase of involucrin.

RESULTS

Under acute irradiation, cell viability and morphology were not altered. However, a general increase of phosphatidylcholines (PC) phosphatidylethanolamines (PE) and phosphatidylglycerol (PG) together with a slight sphingomyelin (SM) decrease were found in UV irradiated cells, among other changes. In addition, keratinocyte cultures did not present any differentiation hallmark. Contrary to acute-irradiated cells, in chronic exposures, cell viability was reduced and keratinocytes presented an altered morphology. Also, hallmarks of differentiation, such as the increase of involucrin protein and the autophagy induction were detected. Among the main lipid changes that accompanied this phenotype, the increase of long-chain ceramides, lysoPC and glycerolipid species were found.

CONCLUSION

Important lipid changes were detected under acute and chronic UV irradiation. The lipid profile under chronic exposure may represent a lipid fingerprint of the keratinocyte differentiation phenotype.

Untargeted lipidomic analysis of primary human epidermal melanocytes acutely and chronically exposed to UV radiation

Ultraviolet (UV) radiation present in sunlight has been related to harmful effects on skin such as premature aging and skin cancer.

Omics in Zebrafish Teratogenesis

The genome revolution represents a complete change on our view of biological systems. The quantitative determination of changes in all major molecular components of the living cells, the "omics" approach, opened whole new fields for all health sciences. Genomics, transcriptomics, proteomics, metabolomics, and others, together with appropriate prediction and modeling tools, will mark the future of developmental toxicity assessment both for wildlife and humans. This is especially true for disciplines, like teratology, which rely on studies in model organisms, as studies at lower levels of organization are difficult to implement. Rodents and frogs have been the favorite models for studying human reproductive and developmental disorders for decades. Recently, the study of the development of zebrafish embryos (ZE) is becoming a major alternative tool to adult animal testing. ZE intrinsic characteristics makes this model a unique system to analyze in vivo developmental alterations that only can be studied applying in toto approaches. Moreover, under actual legislations, ZE is considered as a replacement model (and therefore, excluded from animal welfare regulations) during the first 5 days after fertilization. Here we review the most important components of the zebrafish toolbox available for analyzing early stages of embryotoxic events that could eventually lead to teratogenesis.