Comparison of Single Phase and Biphasic Extraction Protocols for Lipidomic Studies Using Human Plasma

Extraction and untargeted analysis of metabolome from undemineralised cortical bone matrix

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) untargeted metabolomics has become the gold standard for the profiling of low-molecular-weight compounds. Recently, this discipline has raised great interest in forensic sciences, especially in the field of toxicology and for post-mortem interval estimation. The current study aims at evaluating three extraction protocols and two LC-MS/MS assays run in both positive and negative modes, to identify the most suitable method to conduct post-mortem metabolomic profiling of bone tissue. A fragment of the anterior tibia of a 82 years-old male sampled from a human taphonomy facility was powdered via freeze-milling. The powdered sub-samples were extracted in five replicates per protocol. Methods tested were (I) a biphasic chloroform-methanol-water protocol, (II) a single phase methanol-water protocol, and (III) a single phase methanol-acetonitrile-water protocol. LC-MS/MS analyses were carried out via high performance liquid chromatography, either on hydrophilic interaction (HILIC) or on reversed-phase (C18) columns in both positive and negative ionisation modes, coupled with a Q-TOF mass spectrometer. Results suggest that the highest consistency between replicates and quality control samples was obtained with the single phase extractions (i.e., methanol-acetonitrile-water), whilst the ideal combination of instrumental set up HILIC chromatography in positive ionisation mode and of C18 chromatography in negative ionisation mode. For the purpose of forensic investigations, a combination of a single phase extraction and the two aforementioned chromatographic and mass spectrometry modes could represent an ideal set up for obtaining bone metabolomic profiles from taphonomically altered bones.

Automated preparation of plasma lipids, metabolites, and proteins for LC/MS-based analysis of a high-fat diet in mice

Blood plasma is one of the most commonly analyzed and easily accessible biological samples. Here, we describe an automated liquid-liquid extraction (LLE) platform that generates accurate, precise, and reproducible samples for metabolomic, lipidomic, and proteomic analyses from a single aliquot of plasma while minimizing hands-on time and avoiding contamination from plasticware. We applied mass spectrometry to examine the metabolome, lipidome, and proteome of 90 plasma samples to determine the effects of age, time of day, and a high-fat diet in mice. From 25 μL of mouse plasma, we identified 907 lipid species from 16 different lipid classes and subclasses, 233 polar metabolites, and 344 proteins. We found that the high-fat diet induced only mild changes in the polar metabolome, upregulated Apolipoproteins, and induced substantial shifts in the lipidome, including a significant increase in arachidonic acid (AA) and a decrease in eicosapentaenoic acid (EPA) content across all lipid classes.

Proteomic and metabolomic profiling of methicillin resistant versus methicillin sensitive Staphylococcus aureus using a simultaneous extraction protocol

Background

Understanding the biology of methicillin resistant Staphylococcus aureus (MRSA) is crucial to unlocking insights for new targets in our fight against this antimicrobial resistant priority pathogen. Although proteomics and metabolomic profiling offer the potential to elucidating such biological markers, reports of methodological approaches for carrying this out in S. aureus isolates remain limited. We describe the use of a dual-functionality methanol extraction method for the concurrent extraction of protein and metabolites from S. aureus and report on the comparative analysis of the proteomic and metabolomic profiles of MRSA versus methicillin sensitive S. aureus (MSSA).

Methods

Bacterial reference strains MRSA ATCC43300 and MSSA ATCC25923 were used. The conventional urea methodology was used for protein extraction and a methanol based method was used for concurrent proteins and metabolites extraction. Proteomic and metabolomic profiling was carried out using TimsTOF mass spectrometry. Data processing was carried out using the MaxQuant version 2.1.4.0.

Results

This study represents the first report on the utilization of the methanol extraction method for concurrent protein and metabolite extraction in Gram positive bacteria. Our findings demonstrate good performance of the method for the dual extraction of proteins and metabolites from S. aureus with demonstration of reproducibility. Comparison of MRSA and MSSA strains revealed 407 proteins with significantly different expression levels. Enrichment analysis of those proteins revealed distinct pathways involved in fatty acid degradation, metabolism and beta-lactam resistance. Penicillin-binding protein PBP2a, the key determinant of MRSA resistance, exhibited distinct expression patterns in MRSA isolates. Metabolomic analysis identified 146 metabolites with only one exclusive to the MRSA. The enriched pathways identified were related to arginine metabolism and biosynthesis.

Conclusion

Our findings demonstrate the effectiveness of the methanol-based dual-extraction method, providing simultaneous insights into the proteomic and metabolomic landscapes of S. aureus strains. These findings demonstrate the utility of proteomic and metabolomic profiling for elucidating the biological basis of antimicrobial resistance.

A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research

Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.

Studies of Labware Contamination during Lipid Extraction in Mass Spectrometry-Based Lipidome Analysis

In lipidomic analysis, plasticware is increasingly being used for lipid extraction and other sample processing procedures over glassware. However, a systematic investigation of the consequences of plasticware use on mass spectrometry (MS)-based lipidome analysis is lacking. In this work, we present an analytical approach for detecting and comparing solvent and labware contaminants encountered in lipidomic workflows. It is shown that the contaminant profiles varied widely between microcentrifuge tubes from different manufacturers. The most suitable polypropylene tubes tested introduced 847 labware-originating contaminant m/z's when three different manufacturing batches were tested for Folch lipid extractions. Of particular concern is that 21 primary amide and fatty acid surfactants were introduced that were identical to biological endogenous lipids, 16 of which had not been previously reported as leachables from polypropylene materials. Alternatively, the use of borosilicate glassware and PTFE-lined screw caps introduced 98 different contaminant m/z's across three manufacturing batches tested for Folch extractions. Despite the overwhelming number of labware contaminants introduced, current databases and literature only facilitated the identification of 32 contaminants. To address the dearth of publicly available contaminant information, we provide a comprehensive labware contamination repository containing high-resolution m/z values, adductation information, retention times, and MS/MS spectra. This resource should prove to be valuable for researchers in detecting and distinguishing contaminants from analytes of interest. A companion paper presents a detailed study of how labware contamination can lead to ion-suppression effects on coeluting lipids and interference in the analysis of endogenous lipids, such as those from human sera.

HILIC-IM-MS for Simultaneous Lipid and Metabolite Profiling of Bacteria

Although MALDI-ToF platforms for microbial identifications have found great success in clinical microbiology, the sole use of protein fingerprints for the discrimination of closely related species, strain-level identifications, and detection of antimicrobial resistance remains a challenge for the technology. Several alternative mass spectrometry-based methods have been proposed to address the shortcomings of the protein-centric approach, including MALDI-ToF methods for fatty acid/lipid profiling and LC-MS profiling of metabolites. However, the molecular diversity of microbial pathogens suggests that no single "ome" will be sufficient for the accurate and sensitive identification of strain- and susceptibility-level profiling of bacteria. Here, we describe the development of an alternative approach to microorganism profiling that relies upon both metabolites and lipids rather than a single class of biomolecule. Single-phase extractions based on butanol, acetonitrile, and water (the BAW method) were evaluated for the recovery of lipids and metabolites from Gram-positive and -negative microorganisms. We found that BAW extraction solutions containing 45% butanol provided optimal recovery of both molecular classes in a single extraction. The single-phase extraction method was coupled to hydrophilic interaction liquid chromatography (HILIC) and ion mobility-mass spectrometry (IM-MS) to resolve similar-mass metabolites and lipids in three dimensions and provide multiple points of evidence for feature annotation in the absence of tandem mass spectrometry. We demonstrate that the combined use of metabolites and lipids can be used to differentiate microorganisms to the species- and strain-level for four of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa) using data from a single ionization mode. These results present promising, early stage evidence for the use of multiomic signatures for the identification of microorganisms by liquid chromatography, ion mobility, and mass spectrometry that, upon further development, may improve upon the level of identification provided by current methods.

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.

LC-ESI-HRMS - lipidomics of phospholipids : Characterization of extraction, chromatography and detection parameters

Lipids are a diverse class of molecules involved in many biological functions including cell signaling or cell membrane assembly. Owing to this relevance, LC-MS/MS-based lipidomics emerged as a major field in modern analytical chemistry. Here, we thoroughly characterized the influence of MS and LC settings - of a Q Exactive HF operated in Full MS/data-dependent MS2 TOP N acquisition mode - in order to optimize the semi-quantification of polar lipids. Optimization of MS-source settings improved the signal intensity by factor 3 compared to default settings. Polar lipids were separated on an ACQUITY Premier CSH C18 reversed-phase column (100 × 2.1 mm, 1.7 µm, 130 Å) during an elution window of 28 min, leading to a sufficient number of both data points across the chromatographic peaks, as well as MS2 spectra. Analysis was carried out in positive and negative ionization mode enabling the detection of a broader spectrum of lipids and to support the structural characterization of lipids. Optimal sample preparation of biological samples was achieved by liquid-liquid extraction using MeOH/MTBE resulting in an excellent extraction recovery > 85% with an intra-day and inter-day variability < 15%. The optimized method was applied on the investigation of changes in the phospholipid pattern in plasma from human subjects supplemented with n3-PUFA (20:5 and 22:6). The strongest increase was observed for lipids bearing 20:5, while 22:4 bearing lipids were lowered. Specifically, LPC 20:5_0:0 and PC 16:0_20:5 were found to be strongest elevated, while PE 18:0_22:4 and PC 18:2_18:2 were decreased by n3-PUFA supplementation. These results were confirmed by targeted LC-MS/MS using commercially available phospholipids as standards.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Study of sample preparation influence on bacterial lipids profile in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Lipids are one of the cell components therefore it is important to be able to accurately assess them. One of the analytical techniques used to study lipid profiles is matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The present study attempted to select optimal conditions for sample preparation and MALDI MS analysis of bacterial lipidome in both positive and negative ion modes using different extraction protocols-Folch, Matyash, and Bligh & Dyer, solvents used to apply samples, and matrices such as 9-aminoacridine (9-AA), α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), 2-mercaptobenzothiazole (MBT), and 2,4,6-trihydroxyacetophenone (THAP). The obtained results allowed concluding that DHB or CHCA matrices are suitable for lipid analysis in the positive mode, and in the negative mode THAP or 9-AA. The most appropriate protocol for extracting lipids from bacterial cells was the Bligh & Dyer method in both ionization modes. The use of the solvent TA30, which was a mixture of acetonitrile and 0.1% trifluoroacetic acid in water, provided on the spectra a significant number of signals from lipids in all groups analyzed, such as fatty acyls, glycerolipids, and glycerophospholipids.

Machine learning for predicting diabetic metabolism in the Indian population using polar metabolomic and lipidomic features

AIMS

To identify metabolite and lipid biomarkers of diabetes in the Indian subpopulation in newly diagnosed diabetic and long-term diabetic individuals. To utilize the global polar metabolomic and lipidomic profiles to predict the susceptibility of an individual to diabetes using machine learning algorithms.

MATERIALS AND METHODS

87 individuals, including healthy, newly diabetic, and long-term diabetics on medication, were included in the study. Post consent, their serum was used to isolate polar metabolome and lipidome. NMR and LCMS were used to identify the polar metabolites and lipids, respectively. Statistical analysis was done to determine significantly altered molecules. NMR and LCMS comprehensive data were utilized to generate diabetic models using machine learning algorithms. 10 more individuals (pre-diabetic) were recruited, and their polar metabolomic and lipidomic profiles were generated. Pre-diabetic metabolic profiles were then utilized to predict the diabetic status of the metabolome and lipidome beyond glucose levels.

RESULTS

Mannose, Betaine, Xanthine, Triglyceride (38:1), Sphingomyelin (d63:7), and Phosphatidic acid (37:2) are some of the top key biomarkers of diabetes. The predictive model generated showed the receiver operating characteristic area under the curve (ROC-AUC) as 1 on both test and validation data indicating excellent accuracy. This model then predicted the diabetic closeness of the metabolism of pre-diabetic individuals based on probability scores.

CONCLUSION

Polar metabolic and lipid profile of diabetic individuals is very different from that of healthy individuals. Lipid profile alters before the polar metabolic profile in diabetes-susceptible individuals. Without regard to glucose, the diabetic closeness of the metabolism of any individual can be determined.

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.

Component analysis of fat, oil and grease in wastewater: challenges and opportunities

The presence of fat, oil and grease can lead to blockages in sewer lines, pumps, and treatment plant operations, thereby creating health risks and environmental hazards. These deposits primarily consist of fatty acids, triglycerides and soap, among other components. These three main components are hydrophobic and insoluble in water. The composition of FOG can vary significantly depending on the source, such as food service establishments, households, or industrial processes. Several analytical methods, such as chromatographic, gravimetric, chemical and spectroscopic analysis, are used to measure different FOG components. AOAC, Gerber and APHA are the most commonly utilized standardized analytical methods for measuring FOG components. The AOAC and Gerber methods, which use gas chromatography, tend to provide more accurate results compared to other methods. This can be attributed to GC's ability to measure individual fatty acids in FOG samples by separating and quantifying each compound based on its unique chemical properties, such as volatility, polarity and molecular weight. Similarly, high-performance liquid chromatography is capable of measuring glycerides by separating and quantifying them based on their polarity and molecular weight. This article delves into the challenge of accurately measuring FOG concentrations and evaluates various FOG measurement technologies. The study also discusses the need for standardized methods for FOG measurement, highlighting the importance of understanding FOG deposits and the performance of grease interceptors.

In Search of Complementary Extraction Methods for Comprehensive Coverage of the Escherichia coli Metabolome

Escherichia coli is an invaluable research tool for many fields of biology, in particular for the production of recombinant enzymes. However, the activity of many such recombinant enzymes cannot be determined using standard biochemical assays, as often, the relevant substrates are not known, or the products produced are not detectable. Today, the biochemical footprints of such unknown enzyme activities can be revealed via the analysis of the metabolomes of the recombinant E. coli clones in which they are expressed, using sensitive technologies such as mass spectrometry. However, before any metabolites can be identified, it is necessary to achieve as high a coverage of the potential metabolites present within E. coli as possible. We have therefore analyzed a wide range of different extraction methods against the cell free extracts of various recombinant E. coli clones. The results were analyzed to determine the minimum number of extractions that achieved high recovery and coverage of metabolites. Two methods were selected for further analysis due to their ability to produce not only high numbers of ions, but also wide mass coverage and a high degree of complementarity. One extraction method uses acetonitrile and water, in a 4:1 ratio, which is then dried down and reconstituted in the chromatography running buffer prior to injection onto the chromatography column, and the other extraction method uses a combination of methanol, water and chloroform, in a 3:1:1 ratio, which is injected directly onto the chromatography column. These two extraction methods were shown to be complementary to each other, as regards the respective metabolites extracted, and to cover a large range of metabolites.

Evaluation of Lipid Extraction Protocols for Untargeted Analysis of Mouse Tissue Lipidome

Lipidomics refers to the full characterization of lipids present within a cell, tissue, organism, or biological system. One of the bottlenecks affecting reliable lipidomic analysis is the extraction of lipids from biological samples. An ideal extraction method should have a maximum lipid recovery and the ability to extract a broad range of lipid classes with acceptable reproducibility. The most common lipid extraction relies on either protein precipitation (monophasic methods) or liquid-liquid partitioning (bi- or triphasic methods). In this study, three monophasic extraction systems, isopropanol (IPA), MeOH/MTBE/CHCl3 (MMC), and EtOAc/EtOH (EE), alongside three biphasic extraction methods, Folch, butanol/MeOH/heptane/EtOAc (BUME), and MeOH/MTBE (MTBE), were evaluated for their performance in characterization of the mouse lipidome of six different tissue types, including pancreas, spleen, liver, brain, small intestine, and plasma. Sixteen lipid classes were investigated in this study using reversed-phase liquid chromatography/mass spectrometry. Results showed that all extraction methods had comparable recoveries for all tested lipid classes except lysophosphatidylcholines, lysophosphatidylethanolamines, acyl carnitines, sphingomyelines, and sphingosines. The recoveries of these classes were significantly lower with the MTBE method, which could be compensated by the addition of stable isotope-labeled internal standards prior to lipid extraction. Moreover, IPA and EE methods showed poor reproducibility in extracting lipids from most tested tissues. In general, Folch is the optimum method in terms of efficacy and reproducibility for extracting mouse pancreas, spleen, brain, and plasma. However, MMC and BUME methods are more favored when extracting mouse liver or intestine.

Chemical markers in marine food web: A simple workflow based on methyl tert-butyl ether extraction for fatty acids and stable isotopes assessment in plankton samples

Fatty acids (FAs) are used, often in combination with stable isotopes (SIs), as chemical biomarkers to assess the contribution of different prey to the diet of consumers and define food web structure and dynamics. Extraction of lipids is traditionally carried out using methanol (MeOH) combined with chloroform or dichloromethane, these latter being well-known environmental pollutant and potential carcinogenic agents. Recently, extraction protocols based on methyl tert-butyl ether (MTBE) and MeOH have been proposed as an alternative to halogenated solvents in lipidomic studies. However, no specific investigation has been performed to assess MTBE suitability in marine ecological studies including FA analysis together with SI measurements. We used an analytical workflow for qualitative and quantitative analysis of FAs and SIs in field samples of phytoplankton, zooplankton and the scyphomedusa Pelagia noctiluca, applying MTBE in comparison with chloroform- and dichloromethane-based protocols for total lipid extraction. Our analysis suggested that MTBE is a reliable substitute for lipid extraction in trophic ecology studies in marine planktonic organisms.

A Sphingolipidomic Profiling Approach for Comparing X-ray-Exposed and Unexposed HepG2 Cells

An analytical method based on tandem mass spectrometry-shotgun is presently proposed to obtain sphingolipidomic profiles useful for the characterization of lipid extract from X-ray-exposed and unexposed hepatocellular carcinoma cells (HepG2). To obtain a targeted lipidic profile from a specific biological system, the best extraction method must be identified before instrumental analysis. Accordingly, four different classic lipid extraction protocols were compared in terms of efficiency, specificity, and reproducibility. The performance of each procedure was evaluated using the Fourier-transform infrared spectroscopic technique; subsequently, the quality of extracts was estimated using electrospray ionization tandem mass spectrometry. The selected procedure based on chloroform/methanol/water was successfully used in mass spectrometry-based shotgun sphingolipidomics, allowing for evaluation of the response of cells to X-ray irradiation, the most common anticancer therapy. Using a relative quantitative approach, the changes in the sphingolipid profiles of irradiated cell extracts were demonstrated, confirming that lipidomic technologies are also useful tools for studying the key sphingolipid role in regulating cancer growth during radiotherapy.

Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic steatohepatitis (NASH) is a condition characterized by inflammation and hepatic injury/fibrosis caused by the accumulation of ectopic fats in the liver. Recent advances in lipidomics have allowed the identification and characterization of lipid species and have revealed signature patterns of various diseases. Here, we describe a lipidomics workflow to assess the lipid profiles of liver homogenates taken from a NASH mouse model. The protocol described below was used to extract and analyze the metabolites from the livers of mice with NASH by liquid chromatography-mass spectrometry (LC-MS); however, it can be applied to other tissue homogenate samples. Using this method, over 1,000 species of lipids from five classes can be analyzed in a single run on the LC-MS. Also, partial elucidation of the identity of neutral lipid (triacylglycerides and diacylglycerides) aliphatic chains can be performed with this simple LC-MS setup. Key features Over 1,000 lipid species (sphingolipids, cholesteryl esters, neutral lipids, phospholipids, fatty acids) are analyzed in one run. Analysis of liver lipids in non-alcoholic steatohepatitis (NASH) mouse model. Normal-phase chromatography coupled to a triple quadrupole mass spectrometer.

Aggregating in vitro-grown adipocytes to produce macroscale cell-cultured fat tissue with tunable lipid compositions for food applications

We present a method of producing bulk cell-cultured fat tissue for food applications. Mass transport limitations (nutrients, oxygen, waste diffusion) of macroscale 3D tissue culture are circumvented by initially culturing murine or porcine adipocytes in 2D, after which bulk fat tissue is produced by mechanically harvesting and aggregating the lipid-filled adipocytes into 3D constructs using alginate or transglutaminase binders. The 3D fat tissues were visually similar to fat tissue harvested from animals, with matching textures based on uniaxial compression tests. The mechanical properties of cultured fat tissues were based on binder choice and concentration, and changes in the fatty acid compositions of cellular triacylglyceride and phospholipids were observed after lipid supplementation (soybean oil) during in vitro culture. This approach of aggregating individual adipocytes into a bulk 3D tissue provides a scalable and versatile strategy to produce cultured fat tissue for food-related applications, thereby addressing a key obstacle in cultivated meat production.

No skin off your back: the sampling and extraction of sebum for metabolomics

INTRODUCTION

Sebum-based metabolomics (a subset of "sebomics") is a developing field that involves the sampling, identification, and quantification of metabolites found in human sebum. Sebum is a lipid-rich oily substance secreted by the sebaceous glands onto the skin surface for skin homeostasis, lubrication, thermoregulation, and environmental protection. Interest in sebomics has grown over the last decade due to its potential for rapid analysis following non-invasive sampling for a range of clinical and environmental applications.

OBJECTIVES

To provide an overview of various sebum sampling techniques with their associated challenges. To evaluate applications of sebum for clinical research, drug monitoring, and human biomonitoring. To provide a commentary of the opportunities of using sebum as a diagnostic biofluid in the future.

METHODS

Bibliometric analyses of selected keywords regarding skin surface analysis using the Scopus search engine from 1960 to 2022 was performed on 12th January 2023. The published literature was compartmentalised based on what the work contributed to in the following areas: the understanding about sebum, its composition, the analytical technologies used, or the purpose of use of sebum. The findings were summarised in this review.

RESULTS

Historically, about 15 methods of sampling have been used for sebum collection. The sample preparation approaches vary depending on the analytes of interest and are summarised. The use of sebum is not limited to just skin diseases or drug monitoring but also demonstrated for other systemic disease. Most of the work carried out for untargeted analysis of metabolites associated with sebum has been in the recent two decades.

CONCLUSION

Sebum has a huge potential beyond skin research and understanding how one's physiological state affects or reflects on the skin metabolome via the sebaceous glands itself or by interactions with sebaceous secretion, will open doors for simpler biomonitoring. Sebum acts as a sink to environmental metabolites and has applications awaiting to be explored, such as biosecurity, cross-border migration, localised exposure to harmful substances, and high-throughput population screening. These applications will be possible with rapid advances in volatile headspace and lipidomics method development as well as the ability of the metabolomics community to annotate unknown species better. A key issue with skin surface analysis that remains unsolved is attributing the source of the metabolites found on the skin surface before meaningful biological interpretation.

Matrix-assisted laser desorption/ionization-Fourier-transform ion cyclotron resonance-mass spectrometry analysis of exosomal lipids from human serum

RATIONALE

Exosomes contain biomarkers such as proteins and lipids that help in understanding normal physiology and diseases. Lipids, in particular, are infrequently studied using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for biomarker discovery. In this study, MALDI was equipped with a high-resolution MS to investigate exosomal lipids from human serum.

METHODS

Exosomal lipids were profiled using MALDI with Fourier-transform ion cyclotron resonance (FTICR)-MS. Four matrices (i.e., α-cyano-4-hydroxycinnamic acid [CHCA], 2,5-dihydroxybenzoic acid, sinapinic acid, and graphene oxide [GO]) and three sample preparation methods (i.e., dried droplet, thin layer, and two layer) were compared for the number of lipid species detected and the relative abundance of each lipid from human serum and human serum exosomes.

RESULTS

In sum, 172 and 89 lipid species were identified from human serum and human serum exosomes, respectively, using all the methods. The highest number of exosome lipid species, 69, was detected using the CHCA matrix, whereas only 8 exosome lipid species were identified using the GO matrix. Among the identified lipid species, phosphatidylcholine was identified most frequently, probably due to the use of a positive ion mode.

CONCLUSIONS

Exosomes and human serum showed comparable lipid profiles as determined using MALDI-FTICR-MS. These findings provide a new perspective on exosomal lipidomics analysis and may serve as a foundation for future lipidomics-based biomarker research using MALDI-FTICR-MS.

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

Molecular insights into sex-specific metabolic alterations in Alzheimer's mouse brain using multi-omics approach

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by altered cellular metabolism in the brain. Several of these alterations have been found to be exacerbated in females, known to be disproportionately affected by AD. We aimed to unravel metabolic alterations in AD at the metabolic pathway level and evaluate whether they are sex-specific through integrative metabolomic, lipidomic, and proteomic analysis of mouse brain tissue.

METHODS

We analyzed male and female triple-transgenic mouse whole brain tissue by untargeted mass spectrometry-based methods to obtain a molecular signature consisting of polar metabolite, complex lipid, and protein data. These data were analyzed using multi-omics factor analysis. Pathway-level alterations were identified through joint pathway enrichment analysis or by separately evaluating lipid ontology and known proteins related to lipid metabolism.

RESULTS

Our analysis revealed significant AD-associated and in part sex-specific alterations across the molecular signature. Sex-dependent alterations were identified in GABA synthesis, arginine biosynthesis, and in alanine, aspartate, and glutamate metabolism. AD-associated alterations involving lipids were also found in the fatty acid elongation pathway and lysophospholipid metabolism, with a significant sex-specific effect for the latter.

CONCLUSIONS

Through multi-omics analysis, we report AD-associated and sex-specific metabolic alterations in the AD brain involving lysophospholipid and amino acid metabolism. These findings contribute to the characterization of the AD phenotype at the molecular level while considering the effect of sex, an overlooked yet determinant metabolic variable.

Lutein-Fortified Plant-Based Egg Analogs Designed to Improve Eye Health: Formation, Characterization, In Vitro Digestion, and Bioaccessibility

Lutein is a carotenoid found in real eggs that has been reported to have beneficial effects on eye health by reducing the risk of age-related macular degeneration. However, lutein is not often included in plant based (PB) egg analogs. It would, therefore, be advantageous to fortify PB eggs with this health-promoting carotenoid. Moreover, lutein is a natural pigment with a bright red to yellowish color depending on its concentration and environment. It can, therefore, also be used as a plant-based pigment to mimic the desirable appearance of egg yolk. Some of the main challenges to using lutein as a nutraceutical and pigment in PB foods are its poor water-solubility, chemical stability, and bioavailability. In this study, we encapsulated lutein in oil-in-water emulsions, which were then utilized to formulate whole egg analogs. Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) protein isolated from a sustainable plant-based source (duckweed) was used to mimic the thermally irreversible heat-set gelling properties of globular egg proteins, with the aim of obtaining a similar cookability and texture as real eggs. The lutein content (80 mg/100 g) of the egg analogs was designed to be at a level where there should be health benefits. The protein (12.5 wt.%) and oil (10 wt.%) contents of the egg analogs were selected to match those of real egg. The effects of oil droplet size and oil type on the bioaccessibility of the encapsulated lutein were examined using the INFOGEST in vitro digestion model. For the emulsions formulated with long chain triglycerides (LCTs, corn oil), lutein bioaccessibility significantly increased when the initial droplet diameter decreased from around 10 to 0.3 μm, which was attributed to more rapid and complete digestion of the lipid phase for smaller droplets. For medium chain triglycerides (MCTs), however, no impact of droplet size on lutein bioaccessibility was observed. A high lutein bioaccessibility (around 80%) could be obtained for both LCTs and MCTs emulsions containing small oil droplets. Thus, both types of oil can be good carriers for lutein. In summary, we have shown that lutein-fortified PB eggs with good digestibility and bioaccessibility can be created, which may play an important role in ensuring the health of those adopting a more plant-based diet.

An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and Its Application in Gastrointestinal Disease

Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn's disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC.

An Update on Sphingolipidomics: Is Something Still Missing? Some Considerations on the Analysis of Complex Sphingolipids and Free-Sphingoid Bases in Plasma and Red Blood Cells

The main concerns in targeted “sphingolipidomics” are the extraction and proper handling of biological samples to avoid interferences and achieve a quantitative yield well representing all the sphingolipids in the matrix. Our work aimed to compare different pre-analytical procedures and to evaluate a derivatization step for sphingoid bases quantification, to avoid interferences and improve sensitivity. We tested four protocols for the extraction of sphingolipids from human plasma, at different temperatures and durations, and two derivatization procedures for the conversion of sphingoid bases into phenylthiourea derivatives. Different columns and LC-MS/MS chromatographic conditions were also tested. The protocol that worked better for sphingolipids analysis involved a single-phase extraction in methanol/chloroform mixture (2:1, v/v) for 1 h at 38 °C, followed by a 2 h alkaline methanolysis at 38 °C, for the suppression of phospholipids signals. The derivatization of sphingoid bases promotes the sensibility of non-phosphorylated species but we proved that it is not superior to a careful choice of the appropriate column and a full-length elution gradient. Our procedure was eventually validated by analyzing plasma and erythrocyte samples of 20 volunteers. While both extraction and methanolysis are pivotal steps, our final consideration is to analyze sphingolipids and sphingoid bases under different chromatographic conditions, minding the interferences.

Tip-tip filtration ameliorates single-phase extraction methods for plasma large-scale lipidomics analysis

We evaluated the performance of three different single-phase extraction methods to be used before untargeted lipidomics analysis by Liquid Chromatography High-Resolution Mass Spectrometry. Lipids were extracted from a pool of healthy human donors' plasma in triplicates and run in both positive and negative ESI. The most satisfactory results were attained using methanol/chloroform (2:1, v/v) mixture. Eventually, we evaluated whether a filtration of the samples could be beneficial to yield cleaner and more mass-friendly extracts. Instead of using syringes, we set up a method we called tip-tip filtration, which requires the usage of a filtrating pipette tip. This way of purification led to superior results than the solvent extraction method alone. This additional procedure not only increased reproducibility but also allowed the same lipid coverage. In addition, it permitted to spare time and money, as tip-tip filtration is not particularly expensive nor time-consuming and hopefully it may be useful to increase analytical column lifetime.

Comparison of one-phase and two-phase extraction methods for porcine tissue lipidomics applying a fast and reliable tentative annotation workflow

Lipidomics has great potential for the discovery of biomarkers, elucidation of metabolic processes and identifying dysregulations in complex biological systems. Concerning biofluids like plasma or cerebrospinal fluid, several studies for the comparison of lipid extraction solvents have already been conducted. With respect to tissues, which can differ significantly in terms of dry matter content and composition, only few studies are available. The proper selection of an extraction method that covers the complexity and individuality of different tissues is challenging. The goal of this work was to provide a systematic overview on the potential of different extraction methods for a broad applicability. This study covers six different extraction procedures and four different reconstitution solvents applied to ten different porcine tissues. To get an overview of the individual lipid profiles, a workflow was developed for a fast and reliable tentative lipid annotation. Therefore, several machine learning tools were utilized, like the prediction of collision cross sections to support the tentative lipid identification in case of untargeted lipidomics. In terms of data evaluation, unsupervised (e.g. principal component analysis) and supervised (e.g. partial least square - discriminant analysis) methods were applied to visualize and subsequently interpret all generated information. Furthermore, the influence of the tissue composition on the extraction performance was investigated. It could be shown that the ten porcine tissues can be distinguished based on their lipid profile with the applied workflow and that the methyl-tert-butyl ether (MTBE) based extraction method (two-phase) showed the best overall performance for the 16 examined lipid species. With this method the highest number of features (428 in lung tissue) could be annotated. Upcoming one-phase extractions also showed a high potential concerning total number of extracted lipids. Methanol/MTBE/chloroform (MMC) extracted slightly less lipids (393 in lung and liver) than MTBE but turned out to be the best one-phase extraction method. Additionally, the numbers of extracted lipids obtained by isopropanol/water 90:10 (IPA90) (399 in stomach) and by isopropanol/methanol/chloroform (IMC) (395 in stomach) were similar to those of the modified Folch method (402 in stomach). One-phase extractions can therefore clearly be seen as preferable when a high throughput is needed.

Advances in Lipid Extraction Methods-A Review

Extraction of lipids from biological tissues is a crucial step in lipid analysis. The selection of appropriate solvent is the most critical factor in the efficient extraction of lipids. A mixture of polar (to disrupt the protein-lipid complexes) and nonpolar (to dissolve the neutral lipids) solvents are precisely selected to extract lipids efficiently. In addition, the disintegration of complex and rigid cell-wall of plants, fungi, and microalgal cells by various mechanical, chemical, and enzymatic treatments facilitate the solvent penetration and extraction of lipids. This review discusses the chloroform/methanol-based classical lipid extraction methods and modern modifications of these methods in terms of using healthy and environmentally safe solvents and rapid single-step extraction. At the same time, some adaptations were made to recover the specific lipids. In addition, the high throughput lipid extraction methodologies used for liquid chromatography-mass spectrometry (LC-MS)-based plant and animal lipidomics were discussed. The advantages and disadvantages of various pretreatments and extraction methods were also illustrated. Moreover, the emerging green solvents-based lipid extraction method, including supercritical CO2 extraction (SCE), is also discussed.

Clinical lipidomics: realizing the potential of lipid profiling

Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration-assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.

Analytical considerations for reducing the matrix effect for the sphingolipidome quantification in whole blood

Aim: Plasma and serum are widely used blood-derived biofluids for metabolomics and lipidomics assays, but analytes that are present in high concentrations in blood cells cannot be evaluated in those samples and isolating serum or plasma could introduce additional variability in the data. Materials & methods: In this study, we provide a comprehensive method for quantification of the whole blood (WB) sphingolipidome, combining a single-phase extraction method with LC-high-resolution mass spectrometry. Results: We were able to quantify more than 150 sphingolipids, and when compared with paired plasma, WB contained higher concentration of most sphingolipids and individual variations were lower. These findings suggest that WB could be a better alternative to plasma, and potentially guide the evaluation of the sphingolipidome for biomarker discovery.

There is detectable variation in the lipidomic profile between stable and progressive patients with idiopathic pulmonary fibrosis (IPF)

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease characterized by fibrosis and progressive loss of lung function. The pathophysiological pathways involved in IPF are not well understood. Abnormal lipid metabolism has been described in various other chronic lung diseases including asthma and chronic obstructive pulmonary disease (COPD). However, its potential role in IPF pathogenesis remains unclear.

Methods

In this study, we used ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to characterize lipid changes in plasma derived from IPF patients with stable and progressive disease. We further applied a data-independent acquisition (DIA) technique called SONAR, to improve the specificity of lipid identification.

Results

Statistical modelling showed variable discrimination between the stable and progressive subjects, revealing differences in the detection of triglycerides (TG) and phosphatidylcholines (PC) between progressors and stable IPF groups, which was further confirmed by mass spectrometry imaging (MSI) in IPF tissue.

Conclusion

This is the first study to characterise lipid metabolism between stable and progressive IPF, with results suggesting disparities in the circulating lipidome with disease progression.

Investigating metabolism by mass spectrometry: From steady state to dynamic view

Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

A comprehensive comparison of four methods for extracting lipids from Arabidopsis tissues

BACKGROUND

The plant lipidome is highly complex, and the composition of lipids in different tissues as well as their specific functions in plant development, growth and stress responses have yet to be fully elucidated. To do this, efficient lipid extraction protocols which deliver target compounds in solution at concentrations adequate for subsequent detection, quantitation and analysis through spectroscopic methods are required. To date, numerous methods are used to extract lipids from plant tissues. However, a comprehensive analysis of the efficiency and reproducibility of these methods to extract multiple lipid classes from diverse tissues of a plant has not been undertaken.

RESULTS

In this study, we report the comparison of four different lipid extraction procedures in order to determine the most effective lipid extraction protocol to extract lipids from different tissues of the model plant Arabidopsis thaliana.

CONCLUSION

While particular methods were best suited to extract different lipid classes from diverse Arabidopsis tissues, overall a single-step extraction method with a 24 h extraction period, which uses a mixture of chloroform, isopropanol, methanol and water, was the most efficient, reproducible and the least labor-intensive to extract a broad range of lipids for untargeted lipidomic analysis of Arabidopsis tissues. This method extracted a broad range of lipids from leaves, stems, siliques, roots, seeds, seedlings and flowers of Arabidopsis. In addition, appropriate methods for targeted lipid analysis of specific lipids from particular Arabidopsis tissues were also identified.

Single-Step Extraction Coupled with Targeted HILIC-MS/MS Approach for Comprehensive Analysis of Human Plasma Lipidome and Polar Metabolome

Expanding metabolome coverage to include complex lipids and polar metabolites is essential in the generation of well-founded hypotheses in biological assays. Traditionally, lipid extraction is performed by liquid-liquid extraction using either methyl-tert-butyl ether (MTBE) or chloroform, and polar metabolite extraction using methanol. Here, we evaluated the performance of single-step sample preparation methods for simultaneous extraction of the complex lipidome and polar metabolome from human plasma. The method performance was evaluated using high-coverage Hydrophilic Interaction Liquid Chromatography-ESI coupled to tandem mass spectrometry (HILIC-ESI-MS/MS) methodology targeting a panel of 1159 lipids and 374 polar metabolites. The criteria used for method evaluation comprised protein precipitation efficiency, and relative MS signal abundance and repeatability of detectable lipid and polar metabolites in human plasma. Among the tested methods, the isopropanol (IPA) and 1-butanol:methanol (BUME) mixtures were selected as the best compromises for the simultaneous extraction of complex lipids and polar metabolites, allowing for the detection of 584 lipid species and 116 polar metabolites. The extraction with IPA showed the greatest reproducibility with the highest number of lipid species detected with the coefficient of variation (CV) < 30%. Besides this difference, both IPA and BUME allowed for the high-throughput extraction and reproducible measurement of a large panel of complex lipids and polar metabolites, thus warranting their application in large-scale human population studies.

Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins

The critical role of blood lipids in a broad range of health and disease states is well recognised but less explored is the interplay of genetics and environment within the broader blood lipidome. We examined heritability of the plasma lipidome among healthy older-aged twins (75 monozygotic/55 dizygotic pairs) enrolled in the Older Australian Twins Study (OATS) and explored corresponding gene expression and DNA methylation associations. 27/209 lipids (13.3%) detected by liquid chromatography-coupled mass spectrometry (LC-MS) were significantly heritable under the classical ACE twin model (h2 = 0.28-0.59), which included ceramides (Cer) and triglycerides (TG). Relative to non-significantly heritable TGs, heritable TGs had a greater number of associations with gene transcripts, not directly associated with lipid metabolism, but with immune function, signalling and transcriptional regulation. Genome-wide average DNA methylation (GWAM) levels accounted for variability in some non-heritable lipids. We reveal a complex interplay of genetic and environmental influences on the ageing plasma lipidome.

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.