Recent developments in sample-pretreatment techniques for mass spectrometry-based metabolomics

Rapid characterization of polysaccharides from marine animals using chemical degradation combined with liquid chromatography mass spectrometry

Glycosaminoglycans of marine origin have exceptional biological activities, but rapid elucidation strategies for precise structures are still lacking. In this study, the optimal conditions for deacetylation of glycosaminoglycans were optimized first. The hydrazinolysis time of 24 h was determined as the final condition, oligosaccharides with a degree of polymerization of 2-14 are mainly produced after hydrazinolysis. Then mixed oligosaccharides generated by deacetylation-deamination cleavage of polysaccharides were detected with hydrophilic interaction chromatography with tandem mass spectrometry (HILIC-MS/MS), and the total ion chromatography showed excellent resolution. The mass spectrometry data were automatically processed by GlycReSoft, and the corresponding matching results were obtained according to the set parameters. A small amount of keratan sulfate exists in oligosaccharides of Teuthida and Salmo salar, and ion peaks corresponding to IdoA-GalNAc4S exist in oligosaccharides of Scophthalmus maximus and Salmo salar. The results of the manual analysis of the mass spectrometry data verified that the HILIC-MS/MS combined with automatic analysis by software adopted in this study could achieve accurate matching and matching of mixed oligosaccharide components. The establishment of a rapid and accurate analysis strategy for the structure of glycosaminoglycans in this study will help the development of its application and standardized industrial production.

Advances and challenges in non-targeted analysis: An insight into sample preparation and detection by liquid chromatography-mass spectrometry

Unknown impurities, metabolites and harmful pollutants present in pharmaceutical products, biological and environmental samples, respectively are of high concern in terms of their detection and quantification. The targeted analysis aims to quantify known chemical entities, but it lacks the ability to identify unknown components present in a sample. Non-targeted analysis is an analytical approach that can be made applicable to various disciplines of science to effectively search for unknown chemical, biological, or environmental entities that can answer various baffling mysteries of research. It employs various high-end analytical techniques that can specifically screen out multiple unknown compounds from complex mixtures. Non-targeted analysis is also applicable for complex studies such as metabolomics to search unidentified metabolites of new chemical entities. This review critically discusses the current advancements in non-targeted analysis related to the analysis of pharmaceutical, biological, and environmental samples. Various steps like sample collection, handling, preparation, extraction, its analysis using advanced techniques like high-resolution mass spectrometry, liquid chromatography mass spectrometry, and lastly interpretation of the huge amounts of complex data obtained upon analysis of complex matrices have been discussed broadly in this article. Besides the advantages of non-targeted analysis over targeted analysis, limitations, bioinformatics tools, sources of error, and research gaps have been critically analyzed.

Inhibitory effects of chlorophyll pigments on the bioaccessibility of β-carotene: Influence of chlorophyll structure and oil matrix

Chlorophylls and β-carotene are fat-soluble phytochemicals in daily diets, while their bioaccessibility interaction remains unknown. Eight dietary chlorophylls and their derivatives (chlorophyll a, chlorophyll b, pheophytin a, pheophytin b, chlorophyllide a, chlorophyllide b, pheophorbide a, pheophorbide b) were combined with β-carotene in six different oil matrices (corn oil, coconut oil, medium-chain triglycerides, peanut oil, olive oil and fish oil) and were subjected to in vitro digestion. Generally, chlorophylls significantly decreased β-carotene bioaccessibility by competitive incorporation into micelles. Dephytylated chlorophylls had a greater inhibitory effect on the micellarization and bioaccessibility of β-carotene compared to phytylated chlorophylls. In their co-digestion system, olive oil group exhibited the smallest particle size and biggest zeta potential in both digesta and micelles. For chlorophylls, the phytol group and their levels are key factors, which was also buttressed by the mice model where additional supplementation of pheophorbide a significantly hindered the accumulation of β-carotene and retinoids compounds.

A View on the Chemical and Biological Attributes of Five Edible Fruits after Finishing Their Shelf Life: Studies on Caco-2 Cells

We studied five common perishable fruits in terms of their polyphenols dynamic, minerals distribution, scavenger activity and the effects of 50% ethanolic extracts on the viability of Caco-2 cells in vitro, over a period of time between T = 0 and T = 5/7 days, typically the end of their shelf life. Altogether, there were few changes found, consisting of either an increase or a decrease in their chemical and biological attributes. A slow decrease was found in the antioxidant activity in apricot (-11%), plum (-6%) and strawberry (-4%) extracts, while cherry and green seedless table grape extracts gained 7% and 2% antioxidant potency, respectively; IC50 values ranged from 1.67 to 5.93 μg GAE/μL test extract. The cytotoxicity MTS assay at 24 h revealed the ability of all 50% ethanol fruit extracts to inhibit the Caco-2 cell viability; the inhibitory effects ranged from 49% to 83% and were measured at 28 µg GAE for strawberry extracts/EES, from 22 µg to 45 µg GAE for cherry extracts/EEC, from 7.58 to 15.16 µg GAE for apricot extracts/EEA, from 12.50 to 25.70 µg GAE for plum extracts/EEP and from 21.51 to 28.68 µg GAE for green table grape extracts/EEG. The MTS anti-proliferative assay (72 h) also revealed a stimulatory potency upon the Caco-2 viability, from 34% (EEA, EEG) and 48% (EEC) to 350% (EES) and 690% (EEP); therefore fruit juices can influence intestinal tumorigenesis in humans.

Comprehensive untargeted lipidomic analysis of sea buckthorn using UHPLC-HR-AM/MS/MS combined with principal component analysis

Sea buckthorn is an important ecological and economic plant which has multiple bioactivities. The fruits and seeds of sea buckthorn are rich in oil. However, there are few studies on the differences of lipid profiles of sea buckthorn varieties. Herein, the lipidomic fingerprints of sea buckthorn was established. First, a mixture solvent of methanol and chloroform (2:1, v/v) was selected to extract the lipid of the flesh and seed of sea buckthorn. Then, global lipidomic analysis of different varieties of sea buckthorn was conducted. A total of 16 lipid classes and 112 lipid molecular species were determined. Several molecular species, such as PE (phosphatidylethanolamine) 18:1/18:3, PE18:0/18:1, PE18:0/18:2, etc. were selected as the potential biomarkers to classify the samples. Our study provides a scientific basis for quality control of sea buckthorn and promotes the development of sea buckthorn oil.

Changes in toxicity after mixing imidacloprid and cadmium: enhanced, diminished, or both? From a perspective of oxidative stress, lipid metabolism, and amino acid metabolism in mice

Imidacloprid (IMI) and cadmium (Cd) are pollutants of concern in the environment. Although investigations about their combined toxicity to organisms such as earthworms, aquatic worms, Daphnia magna, and zebrafish have been carried out, their combined toxicity to mammals remains unknow. In this study, twenty-four 8-week-old mice were arbitrarily separated into 4 groups: CK (control group), IMI (15 mg/kg bw/day, 1/10 LD50), Cd (15 mg/kg bw/day, 1/10 LD50), and IMI + Cd (15 mg/kg bw/day IMI + 15 mg/kg bw/d Cd) and the combined toxic effects of IMI and Cd were examined with biochemical (oxidative stress testing) and omics approaches (metabolomics and lipidomics). The results revealed changes in each treatment group in terms of oxidative stress, abnormalities in lipid metabolism, and disturbances in amino acid metabolism. Co-administration had antagonistic effects on MDA accumulation and lipid metabolism disorders while acting synergistically on changes in SOD and GSH-Px activities. It is worth noting that after analysis, the changes caused by mixed administration in vivo were closer to those caused by IMI administration alone. This study provides new insights into the combined toxicity of neonicotinoids and heavy metals, which is helpful for relevant environmental governance and further investigations about their impacts on human health and the environment.

Metabolomics in archaeological science: A review of their advances and present requirements

Metabolomics, the study of metabolites (small molecules of <1500 daltons), has been posited as a potential tool to explore the past in a comparable manner to other omics, e.g., genomics or proteomics. Archaeologists have used metabolomic approaches for a decade or so, mainly applied to organic residues adhering to archaeological materials. Because of advances in sensitivity, resolution, and the increased availability of different analytical platforms, combined with the low mass/volume required for analysis, metabolomics is now becoming a more feasible choice in the archaeological sector. Additional approaches, as presented by our group, show the versatility of metabolomics as a source of knowledge about the human past when using human osteoarchaeological remains. There is tremendous potential for metabolomics within archaeology, but further efforts are required to position it as a routine technique.

Miniaturization and Automation Protocol of a Urinary Organic Acid Liquid-Liquid Extraction Method on GC-MS

The aim of this study was to improve the extraction method for urinary organic acids by miniaturizing and automating the process. Currently, manual extraction methods are commonly used, which can be time-consuming and lead to variations in test results. To address these issues, we reassessed and miniaturized the in-house extraction method, reducing the number of steps and the sample-to-solvent volumes required. The evaluated miniaturized method was translated into an automated extraction procedure on a MicroLab (ML) Star (Hamilton Technologies) liquid handler. This was then validated using samples obtained from the ERNDIM External Quality Assurance program. The organic acid extraction method was successfully miniaturized and automated using the Autosampler robot. The linear range for most of the thirteen standard analytes fell between 0 to 300 mg/L in spiked synthetic urine, with low (50 mg/L), medium (100 mg/L), and high (500 mg/L) levels. The correlation coefficient (r) for most analytes was >0.99, indicating a strong relationship between the measured values. Furthermore, the automated extraction method demonstrated acceptable precision, as most organic acids had coefficients of variation (CVs) below 20%. In conclusion, the automated extraction method provided comparable or even superior results compared to the current in-house method. It has the potential to reduce solvent volumes used during extraction, increase sample throughput, and minimize variability and random errors in routine diagnostic settings.

A novel magnetic fluid for ultra-fast and highly efficient extraction of N1-methylnicotinamide in urine samples

Among the three pre-treatment materials, Fe3O4@HPMC@DMSA NPs were selected to be the best material and were used to perform MSPE-HPLC-UV.

Simultaneous Analysis of Free/Combined Phytosterols in Rapeseed and Their Dynamic Changes during Microwave Pretreatment and Oil Processing

Here, a simple, efficient, and rapid solid phase extraction-gas chromatography (SPE–GC) method was developed for the simultaneous analysis of free/combined phytosterols in rapeseed and their dynamic changes during microwave pretreatment and oil processing. First, by comparing different methods for extracting free/combined phytosterols from rapeseed and rapeseed cake, the Folch method was considered to be the optimal method and was selected in subsequent experiments. Subsequently, the extraction method was validated by determining the recoveries of standards (brassinosterol, campesterol, β-sitosterol and cholesteryl oleate) spiked in rapeseed and rapeseed oil samples, and the recoveries were in the range from 82.7% to 104.5% and 83.8% to 116.3%, respectively. The established method was applied to study the dynamic changes of the form and content of phytosterols in rapeseed and its products (rapeseed oil and cake) during rapeseed microwave pretreatment and the oil production process. Additionally, the results showed that more than 55% of the free/combined phytosterols in rapeseed were transferred to rapeseed oil during the oil processing, and this proportion will increase after microwave pretreatment of rapeseed. This work will provide analytical methods and data support for a comprehensive understanding of phytosterols in rapeseed and its products during oil processing.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers

Mass spectrometry (MS) is one of the most widely used analytical techniques in many fields. Recent developments in chemical and biological researches have drawn much attention to the measurement of substances with low abundances in samples. Continuous efforts have been made consequently to further improve the sensitivity of MS. Modifications on the mass analyzers of mass spectrometers offer a direct, universal and practical way to obtain higher sensitivity. This review provides a comprehensive overview of the latest developments in mass analyzers for the improvement of mass spectrometers' sensitivity, including quadrupole, ion trap, time-of-flight (TOF) and Fourier transform ion cyclotron (FT-ICR), as well as different combinations of these mass analyzers. The advantages and limitations of different mass analyzers and their combinations are compared and discussed. This review provides guidance to the selection of suitable mass spectrometers in chemical and biological analytical applications. It is also beneficial to the development of novel mass spectrometers.

Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis

The metabolomics approach represents the last downstream phenotype and is widely used in clinical studies and drug discovery. In this paper, we outline recent advances in the metabolomics research of autoimmune diseases (ADs) such as rheumatoid arthritis (RA), multiple sclerosis (MuS), and systemic lupus erythematosus (SLE). The newly discovered biomarkers and the metabolic mechanism studies for these ADs are described here. In addition, studies elucidating the metabolic mechanisms underlying these ADs are presented. Metabolomics has the potential to contribute to pharmacotherapy personalization; thus, we summarize the biomarker studies performed to predict the personalization of medicine and drug response.

Effect of cultivation media and temperature on metabolite profiles of three nematicidal Bacillus species

Globally, root-knot nematode (RKN) infestations cause great financial losses. Although agrochemicals are used to manage these pests, there is increased interest in using biocontrol agents based on natural antagonistic microorganisms, such as Bacillus. These nematicidal bacteria demonstrate antagonism towards RKN through different modes of action, including specialised metabolite production. The aim of this study was to compare metabolite profiles of nematicidal Bacillus species and assess the influence of cultivation conditions on these profiles. Two hyphenated metabolomics platforms, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-QTOF-MS), were employed to profile and compare metabolite features produced during the cultivation of three nematicidal Bacillus species (Bacillus firmus, B. cereus and B. soli) in complex Luria-Bertani broth (LB) and a simpler minimal broth (MB), at three different temperatures (25, 30 and 37°C). Cultivation in complex LB as opposed to simpler MB resulted in the production of more statistically significant metabolite features. Selected temperatures in this study did not have a significant influence on metabolite profiles. Moreover, media-specific influences outweighed temperature-specific influences on metabolite profiles. Results from this study are a valuable first step in establishing suitable cultivation conditions for the production of Bacillus metabolites of interest.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Metabolite Profiling of Dioscorea (Yam) Leaves to Identify Bioactive Compounds Reveals Their Potential as Renewable Resources

Yams (Dioscorea spp.) are cultivated and consumed as edible tubers, while their leaves are discarded as waste or burned with negative environmental impact. Herein, the metabolites of two yam species (Danma, DAN; Dunggeunma, DUN), harvested in June, July, and August, were profiled using GC-TOF-MS and UHPLC-LTQ-Orbitrap-MS/MS and the antioxidant activity of the extracts was evaluated to stimulate the utilization of yam leaves as a by-product. We observed that the relative levels of amino acids, organic acids, sugars, and saponins decreased linearly with prolonged harvest time, while fatty acid, phenanthrene, and flavonoid levels gradually increased. Furthermore, the leaf extracts obtained in August exhibited the highest antioxidant activity. To determine the antioxidant-contributing metabolites, OPLS-DA was performed for the leaf metabolites of DAN and DUN leaves harvested in August. Hydroxytyrosol-glucoside, apigenin-rhamnoside, and rutin were more abundant in DUN, while luteolin, phenanthrene derivatives, epicatechin, and kaempferide were relatively higher in DAN and their respective metabolites were positively correlated with the antioxidant activity. Moreover, secondary metabolites were more abundant in the leaves than in the roots, and consequently, the antioxidant activity of the former was also higher. Overall, the potential value of yam leaves as a renewable source of bioactive compounds is proposed.

Mass spectrometry based high-throughput bioanalysis of low molecular weight compounds: are we ready to support personalized medicine?

Liquid chromatography coupled to mass spectrometry (LC-MS) is the gold standard in bioanalysis for the development of quantitative assays to support drug development or therapeutic drug monitoring. High-throughput and low-cost gene sequencing have enabled a paradigm shift from one treatment fits all to personalized medicine (PM). However, gene monitoring provides only partial information about the health state. The full picture requires the combination of gene monitoring with the screening of exogenous compounds, metabolites, lipids, and proteins. This critical review discusses how mass spectrometry–based technologies and approaches including separation sciences, ambient ionization, and ion mobility are/could be used to support high-throughput bioanalysis of endogenous end exogenous low molecular weight compounds. It includes also various biological sample types (from blood to expired air), and various sample preparation techniques.

Comprehensive and High-Coverage Lipidomic Analysis of Oilseeds Based on Ultrahigh-Performance Liquid Chromatography Coupled with Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Oilseeds are an important source of dietary lipids, and a comprehensive analysis of oilseed lipids is of great significance to human health, while information about the global lipidomes in oilseeds was limited. Herein, an ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry method for comprehensive lipidomic profiling of oilseeds was established and applied. First, the lipid extraction efficiency and lipid coverage of four different lipid extraction methods were compared. The optimized methyl tert-butyl ether extraction method was superior to isopropanol, Bligh-Dyer, and Folch extraction methods, in terms of the operation simplicity, lipid coverage, and number of identified lipids. Then, global lipidomic analysis of soybean, sesame, peanut, and rapeseed was conducted. A total of 764 lipid molecules, including 260 triacylglycerols, 54 diacylglycerols, 313 glycerophospholipids, 36 saccharolipids, 35 ceramides, 30 free fatty acids, 21 fatty esters, and 15 sphingomyelins were identified and quantified. The compositions and contents of lipids significantly varied among different oilseeds. Our results provided a theoretical basis for the selection and breeding of varieties of oilseed as well as deep processing of oilseed for the edible oil industry.

High-Throughput Untargeted Serum Metabolomics Analysis of Hyperuricemia Patients by UPLC-Q-TOF/MS

Hyperuricemia (HUA) as a metabolic disease is closely associated with metabolic disorders. The etiology and pathogenesis of HUA are not fully understood, so there is no radical cure so far. Metabolomics, a specialized study of endogenous small molecule substances, has become a powerful tool for metabolic pathway analysis of selected differential metabolites, which is helpful for initially revealing possible development mechanisms of various human diseases. Twenty HUA patients and 20 healthy individuals participated in the experiment, and ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS) was employed to investigate serum samples to find differential metabolites. The statistical techniques used were principal component analysis and orthogonal partial least-squares discriminant analysis. The differences in metabolomics results of samples after pretreatment with different solvents were compared, 38, 20, 26, 28, 33, 50, and 40 potential differential metabolites were found, respectively, in HUA patient samples, and each group involved different metabolic pathways. Repetitive metabolites were removed, 138 differential metabolites in HUA serum were integrated for analysis, and the human body was affected by 7 metabolic pathways of glycerophospholipid metabolism, sphingolipid metabolism, arachidonic acid metabolism, linoleic acid metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and α-linolenic acid metabolism. In this work, the metabolomics approach based on UPLC-Q-TOF/MS was employed to investigate serum metabolic changes in HUA patients, 138 potential differential metabolites related to HUA were identified, which provided associations of lipids, amino acids, fatty acids, organic acids, and nucleosides profiles of HUA individuals. Metabolic pathways involved in glycerophospholipid metabolism, sphingolipid metabolism, arachidonic acid metabolism, linoleic acid metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and a-linolenic acid metabolism shed light on the understanding of the etiology and pathogenesis process of HUA.

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

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

Exploring metabolic alterations associated with death from asphyxia and the differentiation of asphyxia from sudden cardiac death by GC-HRMS-based untargeted metabolomics

The determination of cause of death is one of the most important tasks in forensic practice. However, asphyxia is a difficult cause of death to determine, especially when the deceased has an underlying disease that can lead to a sudden unexpected death, such as coronary atherosclerotic heart disease (CAHD, which is the leading cause of sudden cardiac death, SCD), because its determination is currently still based on an exclusion strategy. In this study, gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS)-based untargeted metabolomics was employed to obtain the pulmonary metabolic profiles of rats who died from asphyxia and SCD. First, fourteen metabolites were identified to investigate the mechanism of death from asphyxia, and we proposed some explanations that may account for these metabolic alterations, including the perturbation of amino acid metabolism, lipid metabolism, and energy metabolism (TCA cycle). Second, we discovered eight potential biomarkers to differentiate between asphyxia and SCD as the cause of death. The excellent classification performances of the eight individual biomarkers and their combination in fresh lung tissue were observed. Third, we also explored the relative change in the concentration of the eight metabolites and their classification performance in decomposed tissue (at 24 h postmortem). Lactic acid, pantothenic acid, and the combination of the eight biomarkers can be recognized as perfect classifiers to discriminate asphyxia from SCD even when decomposition has occurred. Our results showed that GC-HRMS-based untargeted metabolomics can be used as a promising tool to explore the metabolic alterations of the death process and to determine the cause of death.

Generic multicriteria approach to determine the best precipitation agent for removal of biomacromolecules prior to non-targeted metabolic analysis

The removal of biomacromolecules from biofluids decreases the sample complexity and lower electrospray suppression effects. Furthermore, it can increase the analysis sensitivity, precision, and selectivity. Often removal approaches evaluate the model based on a single criterion, like protein removed or response of one of few specific metabolites. In this study, we used a multicriteria approach to test the effect of using the solvents methanol and acetonitrile (organic solvent precipitation), trichloroacetic acid (acidic precipitation) and ammonium sulphate (salting out) to remove biomacromolecules from a downstream recovery process from a bacillus fermentation. The downstream recovery process intermediates were analysed using reversed-phase ultra-high-pressure liquid chromatography with electrospray ionisation and high-resolution time-of-flight mass spectrometry detection. To evaluate the pre-treatment agents the following multicriteria was applied i) practical considerations, ii) total amino acid in the precipitated pellet, iii) putative identification of the molecules removed or created by the different treatments, iv) coherence between high quality extracted ion chromatograms (repeatability of DW-CODA) and v) replicate consistency from principal component analysis score values obtained by using the CHEMometric analysis of sections of Selected Ion Chromatograms (CHEMSIC) method. This study presents a generic workflow to find the best pre-treatment for removing bio-macromolecules from biofluids with a multicriteria approach. In our case, the best protein removal strategy for downstream recovery intermediates was acetonitrile precipitation. This method showed high precision, created few artefact peaks compared to simple sample dilution, and mainly removed small peptides.

The Use of Gas Chromatography Coupled with High-Resolution Mass Spectrometry-Based Untargeted Metabolomics to Discover Metabolic Changes and Help in the Determination of Complex Causes of Death: A Preliminary Study

The determination of cause of death (COD) is one of the most important tasks in forensic practice and is mainly based on macroscopical and microscopical morphological signatures. However, some CODs are hard to determine because the significant morphological signatures can be nonspecific, variable, subjective, or even absent in the real world. In this study, gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS)-based untargeted metabolomics was employed to obtain plasma metabolic profiles of rats that died from anaphylactic shock (AS), mechanical asphyxia (MA), or sudden cardiac death (SCD). The metabolic alterations of each COD group compared to the control group were investigated using a principal component analysis, partial least-squares discriminant analysis, the Wilcoxon test, and fold change analysis. A range of differential features was screened, and 11, 8, and 7 differential metabolites were finally verified for the AS, MA, and SCD groups, respectively. We proposed some explanations that may account for these metabolic differences, including glucose metabolism, the tricarboxylic acid cycle, glycolysis, lipid metabolism, creatinine catabolism, and purine metabolism. Next, for each COD, we used its differential metabolites, which were obtained through comparisons of each COD group to the control group and represented the metabolic changes of the individual COD, to perform a receiver operating characteristic (ROC) analysis to preliminarily evaluate their ability to discriminate each COD group from the other COD groups. We found that creatinine in the AS group and malic acid and uric acid in the MA group might represent some specific metabolic changes for the relevant COD with high areas under the curve in the ROC curve analysis. Moreover, the combination panel for AS or MA also showed a good ability to discriminate it from the others. However, SCD had fewer metabolic signatures and was relatively harder to discriminate from the other CODs in our work. The preliminary study demonstrates the feasibility of GC-HRMS-based untargeted metabolomics as a promising tool to reveal metabolic changes in different death processes and to determine the complex CODs.

Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review

Arboviruses, such as chikungunya, dengue, yellow fever, and zika, caused by the bite of the Aedes aegypti mosquito, have been a frequent public health problem, with a high incidence of outbreaks in tropical and subtropical countries. These diseases are easily confused with a flu-like illness and present very similar symptoms, difficult to distinguish, and treat appropriately. The effects that these infections cause in the organism are fundamentally derived from complex metabolic processes. A prominent area of science that investigates the changes in the metabolism of complex organisms is the metabolomics. Metabolomics measures the metabolites produced or altered in biological organisms, through the use of robust analytical platforms, such as separation techniques hyphenated with mass spectrometry, combined with bioinformatics. This review article presents an overview of the basic concepts of metabolomics workflow and advances in this field, and compiles research articles that use this omic approach to study these arboviruses. In this context, the metabolomics is applied to search new therapies, understand the viral replication mechanisms, and access the host-virus interactions.

Compensate for or Minimize Matrix Effects? Strategies for Overcoming Matrix Effects in Liquid Chromatography-Mass Spectrometry Technique: A Tutorial Review

In recent decades, mass spectrometry techniques, particularly when combined with separation methods such as high-performance liquid chromatography, have become increasingly important in pharmaceutical, bio-analytical, environmental, and food science applications because they afford high selectivity and sensitivity. However, mass spectrometry has limitations due to the matrix effects (ME), which can be particularly marked in complex mixes, when the analyte co-elutes together with other molecules, altering analysis results quantitatively. This may be detrimental during method validation, negatively affecting reproducibility, linearity, selectivity, accuracy, and sensitivity. Starting from literature and own experience, this review intends to provide a simple guideline for selecting the best operative conditions to overcome matrix effects in LC-MS techniques, to obtain the best result in the shortest time. The proposed methodology can be of benefit in different sectors, such as pharmaceutical, bio-analytical, environmental, and food sciences. Depending on the required sensitivity, analysts may minimize or compensate for ME. When sensitivity is crucial, analysis must try to minimize ME by adjusting MS parameters, chromatographic conditions, or optimizing clean-up. On the contrary, to compensate for ME analysts should have recourse to calibration approaches depending on the availability of blank matrix. When blank matrices are available, calibration can occur through isotope labeled internal standards and matrix matched calibration standards; conversely, when blank matrices are not available, calibration can be performed through isotope labeled internal standards, background subtraction, or surrogate matrices. In any case, an adjusting of MS parameters, chromatographic conditions, or a clean-up are necessary.

Effects of Different Sample Pulverisation Methods on the Extraction of Metabolites from the Fermented Cottonseed Meal Based on UPLC-Q-TOF-MS

The precondition of studying biological sample is to extract sample metabolites by the best pretreatment methods. There is already limited information about pretreatments of fermented feed metabolites. The study compared the extraction effects of different pulverisation methods used in the sample pretreatment process for the extraction of metabolites from cottonseed meal fermented by Lactobacillus acidophilus based on UPLC-Q-TOF-MS. The extraction effects of three pretreatments (non-pulverisation (WF), pulverisation (F), and high-speed homogenisation methods (YJ)) were compared with the numbers of metabolites and the normalised peak areas of the metabolites. The results showed that the number of metabolites extracted with three pulverisation methods were 1745, 1896, 2132 (ESI+ mode) and 1447, 1675, 2073 (ESI- mode), respectively. The number of variable importance plot (VIP) metabolites and the relative peak areas of metabolites showed that the trend was YJ > F > WF. The extraction effect of high-speed homogenisation method was the best way to extract metabolites from the fermented cottonseed meal. This study built a foundation work for the further research of the fermented feed metabolomics.

Effects of harvesting and extraction methods on metabolite recovery from adherently growing mammalian cells

With the wide application of cell metabolomics in many research areas, there is a need to develop an effective procedure for adherent mammalian cell metabolomics that allows for accurate determination of intracellular metabolite levels and easy comparison between multiple studies of a similar application. Here we aimed to compare the efficiencies of different cell harvesting methods and metabolite extraction methods in sample preparation procedures, and to provide a cell sample processing protocol which focuses on maximizing metabolite recovery ranging from polar to lipidic ones. A systematical evaluation of 4 cell harvesting methods and 4 extraction methods was conducted based on human hepatoma HepG2 cells. The impact of different methods on the recoveries of 11 different categories of metabolites was further investigated. The water disruption sample harvesting method provided superior performance to the other 3 harvesting methods, trypsinization, scraping in phosphate buffered saline, and direct solvent scraping, with respect to the recoveries of polar metabolites and lipids. Among the 4 extraction methods, the novel two-phase solvent system extraction method with both methyl tert-butyl ether (MTBE) and 75% 9 : 1 methanol : chloroform showed an absolute advantage with high extraction efficiency for global metabolomics. We showed a metabolite-specific impact of the harvesting method and extraction method on metabolite concentrations. The water disruption sample collection combined with novel two-phase solvent system extraction enabled simultaneous profiling of lipids and metabolites with mixed polarity for sample preparation. Our approach may open up new perspectives toward large-scale comprehensive metabolomic analyses of adherent mammalian cell samples.

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.

Integration of three-phase microelectroextraction sample preparation into capillary electrophoresis

A major strength of capillary electrophoresis (CE) is its ability to inject small sample volumes. However, there is a great mismatch between injection volume (typically <100 nL) and sample volumes (typically 20-1500 µL). Electromigration-based sample preparation methods are based on similar principles as CE. The combination of these methods with capillary electrophoresis could tackle obstacles in the analysis of dilute samples. This study demonstrates coupling of three-phase microelectroextraction (3PEE) to CE for sample preparation and preconcentration of large volume samples while requiring minimal adaptation of CE equipment. In this set-up, electroextraction takes place from an aqueous phase, through an organic filter phase, into an aqueous droplet that is hanging at the capillary inlet. The first visual proof-of-concept for this set-up showed successful extraction using the cationic dye crystal violet (CV). The potential of 3PEE for bioanalysis was demonstrated by successful extraction of the biogenic amines serotonin (5-HT), tyrosine (Tyr) and tryptophan (Trp). Under optimized conditions limits of detection (LOD) were 15 nM and 33 nM for 5-HT and Tyr respectively (with Trp as an internal standard). These LODs are comparable to other similar preconcentration methods that have been reported in conjunction with CE. Good linearity (R² > 0.9967) was observed for both model analytes. RSDs for peak areas in technical replicates, interday and intraday variability were all satisfactory, i.e., below 14%. 5-HT, Tyr and Trp spiked to human urine were successfully extracted and separated. These results underline the great potential of 3PEE as an integrated enrichment technique from biological samples and subsequent sensitive metabolomics analysis.

Experimental Design and Sample Preparation in Forest Tree Metabolomics

Appropriate experimental design and sample preparation are key steps in metabolomics experiments, highly influencing the biological interpretation of the results. The sample preparation workflow for plant metabolomics studies includes several steps before metabolite extraction and analysis. These include the optimization of laboratory procedures, which should be optimized for different plants and tissues. This is particularly the case for trees, whose tissues are complex matrices to work with due to the presence of several interferents, such as oleoresins, cellulose. A good experimental design, tree tissue harvest conditions, and sample preparation are crucial to ensure consistency and reproducibility of the metadata among datasets. In this review, we discuss the main challenges when setting up a forest tree metabolomics experiment for mass spectrometry (MS)-based analysis covering all technical aspects from the biological question formulation and experimental design to sample processing and metabolite extraction and data acquisition. We also highlight the importance of forest tree metadata standardization in metabolomics studies.

A comprehensive analysis of liposomal biomolecular corona upon human plasma incubation: The evolution towards the lipid corona

When drug nanocarriers enter a physiological environment, their surface gets coated by a dynamic biomolecular corona (BMC) mainly constituted by proteins. Although a deep investigation has been performed on the composition of BMC in terms of proteins, scarce attention has been posed to low molecular weight metabolites present in human plasma. In this work, for the first time, the investigation of the BMC of liposomal nanoparticles (NPs) constituted by 1,2-dioleoyl-3-trimethylammonium-propane polar lipid has been carried out by an ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry based untargeted metabolomics approach. Compounds were tentatively identified based on matches with online databases and comparison of MS/MS spectra with available spectral libraries. Moreover, a comparison of three metabolite extraction strategies, including an ultrafiltration membrane based protocol, a methanol extraction based protocol, and Wessel & Flügge protocol, was performed. Methanol extraction procedure resulted in the widest metabolic coverage of liposomal NP BMC. A total of 193 metabolites has been tentatively identified, 166 of which belonged to the class of lipids including phospholipids, steroids, carnitines, fatty alcohols, diglycerides and fatty acids. The high abundance of lipids in the BMC can be explained by the adsorption of plasma lipoproteins onto liposome surface, confirming previous works on other kinds of NPs. Lipids are important bioactive molecules, which could impact NP circulation and uptake by cells. Extending the investigation of BMC beyond the protein corona and towards the "lipid corona" may be the keystone of a better understanding and control of NP fate in human body.

"-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.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

Review of recent developments in GC-MS approaches to metabolomics-based research

BACKGROUND

Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available.

AIM OF REVIEW

This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.

Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.