Comprehensive review of trends and analytical strategies applied for biological samples preparation and storage in modern medical lipidomics: State of the art

Unraveling the complexity of glycosphingolipidome: the key role of mass spectrometry in the structural analysis of glycosphingolipids

Glycosphingolipids (GSL) are a highly heterogeneous class of lipids representing the majority of the sphingolipid category. GSL are fundamental constituents of cellular membranes that have key roles in various biological processes, such as cellular signaling, recognition, and adhesion. Understanding the structural complexity of GSL is pivotal for unraveling their functional significance in a biological context, specifically their crucial role in the pathophysiology of various diseases. Mass spectrometry (MS) has emerged as a versatile and indispensable tool for the structural elucidation of GSL enabling a deeper understanding of their complex molecular structures and their key roles in cellular dynamics and patholophysiology. Here, we provide a thorough overview of MS techniques tailored for the analysis of GSL, emphasizing their utility in probing GSL intricate structures to advance our understanding of the functional relevance of GSL in health and disease. The application of tandem MS using diverse fragmentation techniques, including novel ion activation methodologies, in studying glycan sequences, linkage positions, and fatty acid composition is extensively discussed. Finally, we address current challenges, such as the detection of low-abundance species and the interpretation of complex spectra, and offer insights into potential solutions and future directions by improving MS instrumentation for enhanced sensitivity and resolution, developing novel ionization techniques, or integrating MS with other analytical approaches for comprehensive GSL characterization.

Evaluating the impact of polycyclic aromatic hydrocarbon bioaccumulation in adipose tissue of obese women

Polycyclic aromatic hydrocarbons (PAHs) are widespread across the environment and humans are unavoidably and constantly exposed to them. As lipophilic contaminants, these substances tend to accumulate in fatty tissues as adipose tissue and exposure to these endocrine disruptors has been associated with severe health hazards including prevalence and incidence of obesity. Previous studies have shown significantly higher concentrations of PAHs in adipose tissue compared to other human samples, such as urine and plasma, which are typically used for PAHs assessment. Therefore, conducting biomonitoring studies in adipose tissue is essential, although such studies are currently limited. In this study, the concentrations of 18 PAHs were measured in subcutaneous (scAT) and visceral adipose tissue (vAT) of 188 Portuguese obese females by high performance liquid chromatography (HPLC). The obtained results were then associated with the patient's data namely: 13 clinical, 4 social, and 42 biochemical parameters. Seventeen PAHs were present, at least, in one sample of both scAT and vAT, most of them with detection frequencies higher than 80%. Indeno [1,2,3-cd]pyrene (InP) was the only PAH never detected. Overall higher concentrations of PAHs were observed in scAT. Median concentrations of ∑PAHs were 32.2 ± 10.0 ng/g in scAT and 24.6 ± 10.0 ng/g in vAT. Thirty-six significant associations (7 with social, 18 with clinical, and 11 with biochemical parameters), including 21 Spearman's correlations were identified (12 positive and 9 negative correlations). Indicating the potential effects of PAHs on various parameters such as obesity evolution, body fat, number of adipocytes, total cholesterol, alkaline phosphatase, macrominerals, uric acid, sedimentation velocity, and luteinizing hormone. This study underscores the significance of biomonitoring PAH levels in adipose tissue and their potential effects on metabolic health. Further research is essential to fully comprehend the metabolic implications of PAHs in the human body and to develop strategies for obesity prevention and treatment.

Hollow-fiber liquid phase microextraction for determination of fluoxetine in human serum by nano-liquid chromatography coupled to high resolution mass spectrometry

Therapeutic drug monitoring (TDM) is a personalized care tool based on the determination of a target drug concentration in human serum. An antidepressant drug of interest for such investigations is fluoxetine (FXT), due to a severe impact of genetic polymorphisms on its metabolism. A bioanalytical method employed for TDM purposes must exhibit satisfactory selectivity and detectability, which becomes more difficult due to highly complex biological matrices. In this study, a highly selective bioanalytical method for the determination of FXT in human serum is proposed, which provides excellent clean-up efficiency based on a low cost hollow fiber liquid-phase microextraction (HF-LPME) sample preparation step and nano-liquid chromatography coupled to high-resolution mass spectrometry (nano-LC-HRMS). HF-LPME was performed using a two-phase "U" configuration, with 6 cm fiber, 20 µL of 1-octanol acting as supported liquid membrane, and ammonium hydroxide (pH 10) as the donor phase with NaCl (10 % m/v) and methanol (5 % v/v) as additives, requiring only 250 µL of the sample. The procedure was conducted for 30 min under a 750 rpm stirring rate. Gradient elution was carried out employing an acetonitrile-water as mobile phase, the composition of 30:70 to 100:00 (v/v) for 15 min, using formic acid 0.1 % (v/v) as an additive. MS1 was acquired in an Orbitrap mass analyzer, while MS2 was acquired in a linear trap quadrupole. Satisfactory linearity (Pearson's r = 0.99709) was obtained for a concentration range of 0.02 to 2.5 µg mL-1, which is compatible with the therapeutic and toxic range for FXT. The developed method presents adequate precision (1.61 to 7.45 %) and accuracy (95 to 114 %) and allows the dilution of high concentration samples in a 1:4 ratio (v/v), enabling its application for forensic serum samples. To our knowledge, this is the first study reporting a method based on HF-LPME and nano-LC-HRMS with any analytical purpose, especially with a TDM focus.

Recent Analytical Methodologies in Lipid Analysis

Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

Lipidomics in food quality and authentication: A comprehensive review of novel trends and applications using chromatographic and spectroscopic techniques

Lipid analysis is an integral part of food authentication and quality control which provides consumers with the necessary information to make an informed decision about their lipid intake. Recent advancement in lipid analysis and lipidome scope represents great opportunities for food science. In this review we provide a comprehensive overview of available tools for extraction, analysis and interpretation of data related to dietary fats analyses. Different analytical platforms are discussed including GC, MS, NMR, IR and UV with emphasis on their merits and limitations alongside complementary tools such as chemometric models and lipid-targeted online databases. Applications presented here include quality control, authentication of organic and delicacy food, tracing dietary fat source and investigating the effect of heat/storage on lipids. A multitude of analytical methods with different sensitivity, affordability, reproducibility and ease of operation are now available to comprehensively analyze dietary fats. Application of these methods range from studies which favor the use of large data generating platforms such as MS-based methods, to routine quality control which demands easy to use affordable equipment as TLC and IR. Hence, this review provides a navigation tool for food scientists to help develop an optimal protocol for their future lipid analysis quest.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

Nutritional lipidomics for the characterization of lipids in food

Lipids represent one out of three major macronutrient classes in the human diet. It is estimated to account for about 15-20% of the total dietary intake. Triacylglycerides comprise the majority of them, estimated 90-95%. Other lipid classes include free fatty acids, phospholipids, cholesterol, and plant sterols as minor components. Various methods are used for the characterization of nutritional lipids, however, lipidomics approaches become increasingly attractive for this purpose due to their wide coverage, comprehensiveness and holistic view on composition. In this chapter, analytical methodologies and workflows utilized for lipidomics profiling of food samples are outlined with focus on mass spectrometry-based assays. The chapter describes common lipid extraction protocols, the distinct instrumental mass-spectrometry based analytical platforms for data acquisition, chromatographic and ion-mobility spectrometry methods for lipid separation, briefly mentions alternative methods such as gas chromatography for fatty acid profiling and mass spectrometry imaging. Critical issues of important steps of lipidomics workflows such as structural annotation and identification, quantification and quality assurance are discussed as well. Applications reported over the period of the last 5years are summarized covering the discovery of new lipids in foodstuff, differential profiling approaches for comparing samples from different origin, species, varieties, cultivars and breeds, and for food processing quality control. Lipidomics as a powerful tool for personalized nutrition and nutritional intervention studies is briefly discussed as well. It is expected that this field is significantly growing in the near future and this chapter gives a short insight into the power of nutritional lipidomics approaches.

Probing Herbicide Toxicity to Algae (Selenastrum capricornutum) by Lipid Profiling with Machine Learning and Microchip/MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS)-based lipid profiling is a powerful method to study the cytotoxicity of chemical exposure to microorganisms at the single cell level. We report here a combined approach of machine learning (ML) and microchip-based MALDI-time of flight (TOF) mass spectrometry to investigate the cytotoxic effect of herbicides on algae through single cell lipid profiling. Algal species Selenastrum capricornutum was chosen as the target system, and its exposure to different doses of common chemical herbicides and the resulting cytotoxic behaviors under various stress conditions were characterized. A lipid library for S. capricornutum has been established with 63 identified lipids that include glycosyldiacylglycerols and triacylglycerols. We demonstrated that major alternations occurred for lipids with functional groups of digalactosyldiacylglycerol (DGDG), triacylglycerol (TAG), and monogalactosyldiacylglycerol (MGDG). DGDG was shown to decrease upon exposure to herbicides of norflurazon and atrazine, while some MGDG and TAG lipids would increase for norflurazon. Compared to other algae, S. capricornutum was more strongly impacted by norflurazon than atrazine while the latter was observed to have a greater effect on C. reinhardtii. Machine learning algorithms have been applied to improve the classification of herbicide impact and help identify lipid species affected by the chemical exposure. A total of 69 machine learning models were trained and tested for the identification of ideal algorithms in the classification process, in which flexible discriminant analysis and support vector machine model were found to be the most accurate and consistent. The ML algorithms accurately differentiated herbicide impact and have identified cytotoxic differences that were previously hidden. The results suggest that herbicides express toxicity among different algae likely on the basis of metabolic differences. The ML-assisted method proves to be highly effective and can provide an advanced technological platform for probing cytotoxicity for bacterial species and in metabolic pathway analysis.

Enantioselective metabolomics by liquid chromatography-mass spectrometry

Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.

A Comparison of Lipid Contents in Different Types of Peanut Cultivars Using UPLC-Q-TOF-MS-Based Lipidomic Study

Peanuts are a rich dietary source of lipids, which are essential for human health. In this study, the lipid contents of 13 peanut cultivars were analyzed using UPLC-Q-TOF-MS and GC–MS. The OXITEST reactor was used to test their lipid oxidation stabilities. A total of 27 subclasses, 229 individual lipids were detected. The combined analysis of lipid and oxidation stability showed that lipid unsaturation was inversely correlated with oxidation stability. Moreover, lipid profiles differed significantly among the different peanut cultivars. A total of 11 lipid molecules (TG 18:2/18:2/18:2, TG 24:0/18:2/18:3, TG 20:5/14:1/18:2, TG 18:2/14:1/18:2, PE 17:0/18:2, BisMePA 18:2/18:2, PG 38:5, PMe 18:1/18:1, PC 18:1/18:1, MGDG 18:1/18:1, TG 10:0/10:1/18:1) might be employed as possible indicators to identify high oleic acid (OA) and non-high OA peanut cultivars, based on the PLS-DA result of lipid molecules with a VIP value greater than 2. This comprehensive analysis will help in the rational selection and application of peanut cultivars.

Effects of extraction parameters on lipid profiling of mosses using UPLC-ESI-QTOF-MS and multivariate data analysis

INTRODUCTION

Non-target lipid profiling by using ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOF-MS) has been used extensively in the past decades in plant studies. However, the lipidomes of bryophytes have only been scarcely studied, although they are the second largest group in plant kingdom.

OBJECTIVES

We evaluated the effects of different cell disruption methods (no disruption, shake, ultrasound, and bead beating), and storage conditions (air-dried, freeze-dried, and fresh frozen) of five moss species (including Racomitrium lanuginosum B and D, Philonotis fontana, Sphagnum teres, and Hylocomium splendens).

METHODS

The lipid profiling results of each extraction parameter were analyzed by using multivariate data analysis including unsupervised principal component analysis and supervised orthogonal projections to latent structures discriminant analysis.

RESULTS

The results showed that extraction with bead beating resulted in the highest lipid content and the most detected features, but these were caused by the contamination from plastic tubes. Minor lipid metabolite changes were found in shaking and ultrasonication methods when compared with no disruption method. Significant amounts of phosphatidylcholine, diacylglyceryltrimethylhomoserine and their lyso lipids were observed in air-dried moss tissues, whereas diacylglycerol, triacylglycerol and ceramide were mostly exclusively detected when fresh frozen tissues were used for extraction.

CONCLUSION

We concluded that lipid extraction using fresh frozen samples with ultrasound assistance provide the most original lipid composition and gave a relatively high lipid content.

Comparative liquid chromatography/tandem mass spectrometry lipidomics analysis of macaque heart tissue flash-frozen or embedded in optimal cutting temperature polymer (OCT): Practical considerations

RATIONALE

Biobanks of patient tissues have emerged as essential resources in biomedical research. Optimal cutting temperature compound (OCT) blends have shown to provide stability to the embedded tissue and are compatible with spectroscopic methods, such as infrared (IR) and Raman spectroscopy. Data derived from omics-methods are only useful if tissue damage caused by storage in OCT blends is minimal and well understood. In this context, we investigated the suitability of OCT storage for heart tissue destined for liquid chromatography/tandem mass spectrometry (LC/MS/MS) lipidomic studies.

METHODS

To determine the compatibility of OCT storage with LC/MS/MS lipidomics studies. The lipid profiles of macaque heart tissue snap-frozen in liquid nitrogen or stored in an OCT blend were evaluated.

RESULTS

We have evaluated a lipid extraction protocol suitable for OCT-embedded tissue that is compatible with LC/MS/MS. We annotated and evaluated the profiles of 306 lipid species from tissues stored in OCT or liquid nitrogen. For most of the lipid species (95.4%), the profiles were independent of the storage conditions. However, 4.6% of the lipid species; mainly plasmalogens, were affected by the storage method.

CONCLUSIONS

This study shows that OCT storage is compatible with LC-MS/MS lipidomics of heart tissue, facilitating the use of biobanked tissue samples for future studies.

Lipidomic Profiling of Algae with Microarray MALDI-MS toward Ecotoxicological Monitoring of Herbicide Exposure

Misuse of agrochemicals has a long-lasting negative impact on aquatic systems. Mismanagement of herbicides in agri-food sectors is often linked to a simultaneous decline in the health of downstream waterways. However, monitoring the herbicide levels in these areas is a laborious task, and modern analytical approaches, such as solid-phase extraction-liquid chromatography-mass spectrometry (SPE-LC-MS) and enzyme-linked immunosorbent assay, are low-throughput and require significant sample preparation. We report here the use of microchip technology in combination with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) for the assessment of the ecotoxicological effect of agrochemicals on aquatic species at the single-cell level. This approach quantifies the fluctuations in lipid content in sentinel organisms and targets the microalga, Chlamydomonas reinhardtii (C. reinhardtii), as the model system. Specifically, we investigated the cytotoxicity of three herbicides (atrazine, clomazone, and norflurazon) on C. reinhardtii by analyzing the lipid component variation upon assorted herbicide exposure. Lipidomic profiling reveals a significantly altered lipid content at >EC₅₀ in atrazine-exposed cells. The response for norflurazon showed similar trends but diminished in magnitude, while the result for clomazone was near muted. At lower herbicide concentrations, digalactosyldiacylglycerols showed a rapid decrease in abundance, while several other lipids displayed a moderate increase. The microchip-based MALDI technique demonstrates the ability to achieve lipidomic profiling of aquatic species exposed to different stressors, proving effective for high-throughput screening and single-cell analysis in ecotoxicity studies.

Sample Preparation Methods for Lipidomics Approaches Used in Studies of Obesity

Obesity is associated with alterations in the composition and amounts of lipids. Lipids have over 1.7 million representatives. Most lipid groups differ in composition, properties and chemical structure. These small molecules control various metabolic pathways, determine the metabolism of other compounds and are substrates for the syntheses of different derivatives. Recently, lipidomics has become an important branch of medical/clinical sciences similar to proteomics and genomics. Due to the much higher lipid accumulation in obese patients and many alterations in the compositions of various groups of lipids, the methods used for sample preparations for lipidomic studies of samples from obese subjects sometimes have to be modified. Appropriate sample preparation methods allow for the identification of a wide range of analytes by advanced analytical methods, including mass spectrometry. This is especially the case in studies with obese subjects, as the amounts of some lipids are much higher, others are present in trace amounts, and obese subjects have some specific alterations of the lipid profile. As a result, it is best to use a method previously tested on samples from obese subjects. However, most of these methods can be also used in healthy, nonobese subjects or patients with other dyslipidemias. This review is an overview of sample preparation methods for analysis as one of the major critical steps in the overall analytical procedure.

Mass spectrometry-based untargeted metabolomics approach for differentiation of beef of different geographic origins

Beef is a common staple food in many countries, and there is a growing concern over misinformation of beef products, such as false claims of origin, species and production methods. In this study, we used a mass spectrometry-based metabolomics approach to study the metabolite profiles of beef samples purchased from local retailers in Hong Kong. Using multivariate analysis, beef samples from different a) geographical origins, namely the United States (US), Japan and Australia, and b) feeding regimes could be differentiated. We identified twenty-four metabolites to distinguish beef samples from different countries, ten metabolites to identify Angus beef samples from others and seven metabolites to discriminate Australian beef produced by the organic farming from that produced using other farming modes. Based on results of this study, it is concluded that metabolomics provides an efficient strategy for tracing and authenticating beef products to ensure their quality and to protect consumer rights.

Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review

With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.

Exploring the Lipidome: Current Lipid Extraction Techniques for Mass Spectrometry Analysis

In recent years, high-throughput lipid profiling has contributed to understand the biological, physiological and pathological roles of lipids in living organisms. Across all kingdoms of life, important cell and systemic processes are mediated by lipids including compartmentalization, signaling and energy homeostasis. Despite important advances in liquid chromatography and mass spectrometry, sample extraction procedures remain a bottleneck in lipidomic studies, since the wide structural diversity of lipids imposes a constrain in the type and amount of lipids extracted. Differences in extraction yield across lipid classes can induce a bias on down-stream analysis and outcomes. This review aims to summarize current lipid extraction techniques used for untargeted and targeted studies based on mass spectrometry. Considerations, applications, and limitations of these techniques are discussed when used to extract lipids in complex biological matrices, such as tissues, biofluids, foods, and microorganisms.

Targeting esterified oxylipins by LC-MS - Effect of sample preparation on oxylipin pattern

A major part of oxygenated metabolites of polyunsaturated fatty acids - i.e. eicosanoids and other oxylipins - in biological samples is found in the esterified form. Yet, their biological role is only poorly understood. For quantification of esterified oxylipins in biological samples current protocols mostly apply alkaline hydrolysis with or without prior lipid extraction to release oxylipins into their free form which can be subsequently quantified via liquid chromatography-mass spectrometry. Herein, a detailed protocol for precise and reproducible quantification of esterified oxylipins in plasma is presented comprising i) extraction of lipids and removal of proteins with iso-propanol, ii) base hydrolysis with potassium hydroxide to saponify lipids and iii) solid phase extraction of the liberated oxylipins on C8/anion exchange mixed mode material. Unequal extraction of internal standards and lipid classes during lipid extraction before hydrolysis led to distorted concentrations, emphasizing that the choice of solvent used in this step is important to minimize discrimination. Regarding the hydrolysis conditions, at least 30 min incubation at 60 °C is required with 0.1 M KOH in sample. Drying of the SPE cartridges is a critical parameter since autoxidation processes of PUFA, which are present in high concentrations after cleavage, lead to artificial formation of epoxy fatty acids. With the developed protocol, inter-day, intra-day and inter-operator variance was <21% for most oxylipins including hydroxy-, dihydroxy-, and epoxy-PUFA. The applicability of the developed methodology is demonstrated by investigating the changes in the oxylipin pattern following omega-3 fatty acid feeding to rats.

Toward Single-Organelle Lipidomics in Live Cells

Detailed studies of lipids in biological systems, including their role in cellular structure, metabolism, and disease development, comprise an increasingly prominent discipline called lipidomics. However, the conventional lipidomics tools, such as mass spectrometry, cannot investigate lipidomes until they are extracted, and thus they cannot be used for probing the lipid distribution nor for studying in live cells. Furthermore, conventional techniques rely on the lipid extraction from relatively large samples, which averages the data across the cellular populations and masks essential cell-to-cell variations. Further advancement of the discipline of lipidomics critically depends on the capability of high-resolution lipid profiling in live cells and, potentially, in single organelles. Here we report a micro-Raman assay designed for single-organelle lipidomics. We demonstrate how Raman microscopy can be used to measure the local intracellular biochemical composition and lipidome hallmarks-lipid concentration and unsaturation level, cis/trans isomer ratio, sphingolipids and cholesterol levels in live cells-with a sub-micrometer resolution, which is sufficient for profiling of subcellular structures. These lipidome data were generated by a newly developed biomolecular component analysis software, which provides a shared platform for data analysis among different research groups. We outline a robust, reliable, and user-friendly protocol for quantitative analysis of lipid profiles in subcellular structures. This method expands the capabilities of Raman-based lipidomics toward the analysis of single organelles within either live or fixed cells, thus allowing an unprecedented measure of organellar lipid heterogeneity and opening new quantitative ways to study the phenotypic variability in normal and diseased cells.

"-Omics" workflow for paleolimnological and geological archives: A review

"-Omics" is a powerful screening method with applications in molecular biology, toxicology, wildlife biology, natural product discovery, and many other fields. Genomics, proteomics, metabolomics, and lipidomics are common examples included under the "-omics" umbrella. This screening method uses combinations of untargeted, semi-targeted, and targeted analyses paired with data mining to facilitate researchers' understanding of the genome, proteins, and small organic molecules in biological systems. Recently, however, the use of "-omics" has expanded into the fields of geology, specifically petrology, and paleolimnology. Specifically, untargeted analyses stand to transform these fields as petroleomics, and sediment-"omics" become more prevalent. "-Omics" facilitates the visualization of small molecule profiles from environmental matrices (i.e. oil and sediment). Small molecule profiles can provide improved understanding of small molecules distributions throughout the environment, and how those compositions can change depending on conditions (i.e. climate change, weathering, etc.). "-Omics" also facilities discovery of next-generation biomarkers that can be used for oil source identification and as proxies for reconstructing past environmental changes. Untargeted analyses paired with data mining and multivariate statistical analyses represents a powerful suite of tools for hypothesis generation, and new method development for environmental reconstructions. Here we present an introduction to "-omics" methodology, technical terms, and examples of applications to paleolimnology and petrology. The purpose of this review is to highlight the important considerations at each step in the "-omics" workflow to produce high quality and statistically powerful data for petrological and paleolimnological applications.

A scoring approach for multi-platform acquisition in metabolomics

Since the ultimate goal of untargeted metabolomics is the analysis of the broadest possible range of metabolites, some new metrics have to be used by researchers to evaluate and select different analytical strategies when multi-platform analyses are considered. In this context, we aimed at developing a scoring approach allowing to compare the performance of different LC-MS conditions for metabolomics studies. By taking into account both chromatographic and MS attributes of the analytes' peaks (i.e. retention, signal-to-noise ratio, peak intensity and shape), the newly proposed score reflects the potential of a set of LC-MS operating conditions to provide useful analytical information for a given compound. A chemical library containing 597 metabolites was used as a benchmark to apply this approach on two RPLC and three HILIC methods hyphenated to high resolution mass spectrometry (HRMS) in positive and negative ionization modes. The scores not only allowed to evaluate each analytical platform, but also to optimize the number of analytical methods needed for the analysis of metabolomics samples. As a result, the most informative combination of three LC methods and ionization modes was found, leading to a coverage of nearly 95% of the detected compounds. It was therefore demonstrated that the overall performance reached with three selected methods was almost equivalent to the performance reached when five LC-MS conditions were used.

High-resolution multiple reaction monitoring method for quantification of steroidal hormones in plasma

Multiple reaction monitoring (MRM) is one of the most powerful modes of analysis in liquid chromatographic tandem mass spectrometry for quantification of low-concentration metabolites in biological samples. The advances in mass spectrometry enabled the development of high-resolution multiple reaction monitoring (MRM^HR ) and became suitable for the more specific analysis of target analytes. This is important for lipidomic studies and contributes in the medical and pharmaceutical fields, primarily in investigating alterations in cells or fluids relevant to various diseases. Therefore, this work proposes the development of the MRM^HR method for quantification of circulating steroids. We focused on the determination of corticosterone, 11-dehydrocorticosterone (11-DHC), cortisol, cortisone, aldosterone, and progesterone concentration in serum, by using 129sv male mice exposed to chronic unpredictable stress to validate the quantification. The method was conducted according to the ANVISA normative, adopting a coefficient of variation, as well as relative standard deviation and relative error lower than 15% in linearity, intraday and interday precision, and accuracy. For cortisol, corticosterone, and their inert metabolites (cortisone and 11-DHC), the lower limit of quantification was 3.9 ng· mL^-1 , while that for progesterone and aldosterone was 7.8 and 15.6 ng· mL^-1 , respectively. MRM^HR analysis showed that animals submitted to stressors have 4.5 times more corticosterone in their serum than nonstressed mice. However, 11-DHC concentration does not vary significantly in response to stress for these animals. The results indicate that the method can be applied for quantification of steroids in several biological samples, such as human plasma.