Recent developments and applications of solid phase microextraction as a sample preparation approach for mass-spectrometry-based metabolomics and lipidomics

Metabolomics applications for plant-based foods origin tracing, cultivars identification and processing: Feasibility and future aspects

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression.

In vivo tracing of cyromazine and three neonicotinoids in cowpea under field conditions by solid-phase microextraction combined with ultra-performance liquid chromatography-tandem mass spectrometry

BACKGROUND

Excessive pesticide residues in agricultural products could accumulate in organisms through the food chain, causing potential harm to human health. The investigation of dissipation kinetics and residues of pesticides in crops is crucial for the scientific application of pesticides and the mitigation of their adverse effects on human health. In vivo solid-phase microextraction (in vivo SPME) has unique advantages, but the research on field plants is still lacking and the quantitative correction methods need to be further developed.

RESULTS

A method combining in vivo solid-phase microextraction with ultra-performance liquid chromatography-tandem mass spectrometry (in vivo SPME-UPLC-MS/MS) was developed to monitor the presence of acetamiprid, cyromazine, thiamethoxam and imidacloprid in cowpea fruits grown in the field. The sampling rates (Rs) were determined using both in vitro SPME in homogenized cowpea samples and in vivo SPME in intact cowpea fruit samples. The in vivo-Rs values were significantly higher than the in vitro-Rs for the same analyte, which were used for in vivo SPME correction. The accuracy of this method was confirmed by comparison with a QuEChERS-based approach and subsequently applied to trace pesticide residues in field-grown cowpea fruits. The residual concentrations of each pesticide positively correlated with application doses. After 7 days of application at two different doses, all of the pesticides had residual concentrations below China's maximum residue limits. Both experimental data and predictions indicated that a safe preharvest interval for these pesticides is 7 days; however, if the European Union standards are to be met, a safe preharvest interval for cyromazine should be at least 13 days.

SIGNIFICANCE

This study highlights the advantages of in vivo SPME for simultaneous analysis and tracking of multiple pesticides in crops under field conditions. This technique is environmentally friendly, minimally invasive, highly sensitive, accurate, rapid, user-friendly, cost-effective, and capable of providing precise and timely data for long-term pesticide surveillance. Consequently, it furnishes valuable insights to guide the safe utilization of pesticides in agricultural production.

A review of disrupted biological response associated with volatile organic compound exposure: Insight into identification of biomarkers

Volatile organic compounds (VOCs) are widespread harmful atmospheric pollutants, which have long been concerned and elucidated to be one of the risks of acute and chronic diseases for human, such as leukemia and cancer. Although numerous scientific studies have documented the potential adverse outcomes caused by VOC exposure, the mechanisms which biological response pathways of these VOC disruption remain poorly understood. Therefore, the identification of biochemical markers associated with metabolism, health effects and diseases orientation can be an effective means of screening biological targets for VOC exposure, which provide evidences to the toxicity assessment of compounds. The current review aims to understand the mechanisms underlying VOCs-elicited adverse outcomes by charactering various types of biomarkers. VOCs-related biomarkers from three aspects were summarized through in vitro, animal and epidemiological studies. i) Unmetabolized and metabolized VOC biomarkers in human samples for assessing exposure characteristics in different communities; ii) Adverse endpoint effects related biomarkers, mainly including (anti)oxidative stress, inflammation response and DNA damage; iii) Omics-based molecular biomarkers alteration in gene, protein, lipid and metabolite aspects associated with biological signaling pathway disorders response to VOC exposure. Further research, advanced machine learning and bioinformation approaches combined with experimental results are urgently needed to ascertain the selection of biomarkers and further illuminate toxic mechanisms of VOC exposure. Finally, VOCs-induced disease causes can be predicted with proven results.

Flexible filament winding strategy to prepare COF@polyionic liquid-coated fibers for non-selective exclusion of macromolecules in electro-enhanced solid-phase microextraction

BACKGROUND

Accurate quantitative analysis of small molecule metabolites in biological samples is of great significance. Hydroxypolycyclic aromatic hydrocarbons (OH-PAHs) are metabolic derivatives of emerging pollutants, reflecting exposure to polycyclic aromatic hydrocarbons (PAHs). Macromolecules such as proteins and enzymes in biological samples will interfere with the accurate quantification of OH-PAHs, making direct analysis impossible, requiring a series of complex treatments such as enzymatic hydrolysis. Therefore, the development of matrix-compatible fiber coatings that can exclude macromolecules is of great significance to improve the ability of solid-phase microextraction (SPME) technology to selectively quantify small molecules in complex matrices and achieve rapid and direct analysis.

RESULTS

We have developed an innovative coating with a stable macromolecular barrier using electrospinning and flexible filament winding (FW) technologies. This coating, referred to as the hollow fibrous covalent organic framework@polyionic liquid (F-COF@polyILs), demonstrates outstanding conductivity and stability. It accelerates the adsorption equilibrium time (25 min) for polar OH-PAHs through electrically enhanced solid-phase microextraction (EE-SPME) technology. Compared to the powder form, F-COF@polyILs coating displays effective non-selective large-size molecular sieving. Combining gas chromatography-tandem triple quadrupole mass spectrometry (GC-MS/MS), we have established a simple, efficient quantitative analysis method for OH-PAHs with a low detection limit (0.008-0.05 ng L-1), wide linear range (0.02-1000 ng L-1), and good repeatability (1.0%-7.3 %). Experimental results show that the coated fiber exhibits good resistance to matrix interference (2.5%-16.7 %) in complex biological matrices, and has been successfully used for OH-PAHs analysis in human urine and plasma.

SIGNIFICANCE

FW technology realizes the transformation of the traditional powder form of COF in SPME coating to a uniform non-powder coating, giving its ability to exclude large molecules in complex biological matrices. A method for quantitatively detecting OH-PAHs in real biological samples was also developed. Therefore, the filament winding preparation method for F-COF@polyILs coated fibers, along with fibrous COFs' morphology control, has substantial implications for efficiently extracting target compounds from complex matrices.

Longitudinal characterization of the metabolome of dairy cows transitioning from one lactation to the next: Investigations in the liver

This study aimed to investigate the metabolic changes in the livers of dairy cows from 1 wk before dry off to 1 wk after calving. Twelve high-yielding Holstein cows were included in a longitudinal study and housed in a tiestall barn. The cows were dried off at 6 wk before the expected calving date (dry period length = 42 d). During the entire lactation, the cows were milked twice daily at 0600 and 1700 h. Liver biopsies were taken from each cow at 4 different times: wk -7 (before drying off), -5 (after drying off), -1 and +1 relative to calving. A targeted metabolomics approach was performed by liquid chromatography and flow injection with electrospray ionization triple quadrupole mass spectrometry using the MxP Quant 500 kit (Biocrates Life Sciences AG). A total of 185 metabolites in the liver were used for the final data analysis. Principal component analysis revealed a clear separation by days of sampling, indicating a notable shift in metabolic phenotype from late lactation to the dry period and further changes after calving. Changes were observed in several classes of compounds, including AA and biogenic amines. In particular, the changes in acylcarnitines (AcylCN), phosphatidylcholines (PC), sphingomyelins (SM), and bile acids (BA) indicated extensive remodeling of the hepatic lipidome. The changes in AcylCN concentrations in early lactation suggest incomplete fatty acid oxidation in the liver, possibly indicating mitochondrial dysfunction or enzymatic imbalance. In addition, the changes in PC and SM species in early lactation indicate altered cell membrane composition, which may affect cell signaling and functionality. In addition, changes in BA concentrations and profiles indicate dynamic adaptations in BA synthesis, as well as lipid digestion and absorption during the observation period. In particular, principal component analysis showed an overlapping distribution of liver metabolites in primiparous and multiparous cows, indicating no significant difference between these groups. In addition, Volcano plots showed similar liver metabolism between primiparous and multiparous cows, with no significant fold changes (>1.5) in any metabolite at significant P-values (false discovery rate <0.05). These results provide valuable insight into the physiological ranges of liver metabolites during dry period and calving in healthy dairy cows and should contribute to the design and interpretation of future metabolite-based studies of the transition dairy cow.

Caffeine quantification in dietary supplements using high-throughput on-line solid phase extraction coupled to Venturi easy ambient sonic-spray ionization mass spectrometry

Caffeine is present in a large number of beverages and is an additive used in dietary supplements. Therefore, the concern about its quality and safety for consumers has been increasing and hence requires faster and simpler analytical methods to determine the caffeine amount. The high-throughput analysis is an appropriate solution to pharmaceuticals, bioanalysis, forensic and food laboratory routines. In this sense, Venturi easy ambient sonic-spray ionization mass spectrometry (V-EASI-MS), a specific ambient ionization source, is suitable to enable direct analysis of sample solutions in real time and is appropriate to be coupled to liquid chromatography (LC). The development of an on-line solid phase extraction system coupled to V-EASI-MS optimizes the advantages of LC-MS hyphenation by enhancing the figures of merit of the analytical method according to AOAC guidelines and simultaneously minimizing the runtime analysis to 1.5 min per sample, as well as sample preparation steps and solvent consumption, which is currently a challenge for quantitative applications of ambient ionization MS.

Solid-phase microextraction coupled to comprehensive multidimensional gas chromatography for food analysis

Solid-phase microextraction and comprehensive multidimensional gas chromatography represent two milestone innovations that occurred in the field of separation science in the 1990s. They have a common root in their introduction and have found a perfect coupling in their evolution and applications. This review will focus on food analysis, where the paradigm has changed significantly over time, moving from a targeted analysis, focusing on a limited number of analytes at the time, to a more holistic approach for assessing quality in a larger sense. Indeed, not only some major markers or contaminants are considered, but a large variety of compounds and their possible interaction, giving rise to the field of foodomics. In order to obtain such detailed information and to answer more sophisticated questions related to food quality and authenticity, the use of SPME-GC × GC-MS has become essential for the comprehensive analysis of volatile and semi-volatile analytes. This article provides a critical review of the various applications of SPME-GC × GC in food analysis, emphasizing the crucial role this coupling plays in this field. Additionally, this review dwells on the importance of appropriate data treatment to fully harness the results obtained to draw accurate and meaningful conclusions.

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.

Mapping the metabolic responses to oxaliplatin-based chemotherapy with in vivo spatiotemporal metabolomics

Adjuvant chemotherapy improves the survival outlook for patients undergoing operations for lung metastases caused by colorectal cancer (CRC). However, a multidisciplinary approach that evaluates several factors related to patient and tumor characteristics is necessary for managing chemotherapy treatment in metastatic CRC patients with lung disease, as such factors dictate the timing and drug regimen, which may affect treatment response and prognosis. In this study, we explore the potential of spatial metabolomics for evaluating metabolic phenotypes and therapy outcomes during the local delivery of the anticancer drug, oxaliplatin, to the lung. 12 male Yorkshire pigs underwent a 3 h left lung in vivo lung perfusion (IVLP) with various doses of oxaliplatin (7.5, 10, 20, 40, and 80 mg/L), which were administered to the perfusion circuit reservoir as a bolus. Biocompatible solid-phase microextraction (SPME) microprobes were combined with global metabolite profiling to obtain spatiotemporal information about the activity of the drug, determine toxic doses that exceed therapeutic efficacy, and conduct a mechanistic exploration of associated lung injury. Mild and subclinical lung injury was observed at 40 mg/L of oxaliplatin, and significant compromise of the hemodynamic lung function was found at 80 mg/L. This result was associated with massive alterations in metabolic patterns of lung tissue and perfusate, resulting in a total of 139 discriminant compounds. Uncontrolled inflammatory response, abnormalities in energy metabolism, and mitochondrial dysfunction next to accelerated kynurenine and aldosterone production were recognized as distinct features of dysregulated metabolipidome. Spatial pharmacometabolomics may be a promising tool for identifying pathological responses to chemotherapy.

Metabolomics of natural samples: A tutorial review on the latest technologies

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early-career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early-career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

TiO2@COF-based solid-phase microextraction combined with UHPLC-MS/MS for the rapid determination of potential biomarkers of phosphatidylcholines and lysophosphatidylcholines in head and neck cancers

Phosphatidylcholine (PC) and lysophosphatidylcholine (LPC), two types of phospholipids (PLs), have been reported to be closely correlated with head and neck cancers of laryngeal cancer (LC) and thyroid cancer (TC), which make their analysis crucial. TiO2@COF-based solid-phase microextraction (SPME) coupled to UHPLC-MS/MS was developed for the rapid and accurate detection of seven potential PL biomarkers from small amounts of serum in this work. The combination of TiO2 and COF proves to be effective for the extraction of the target analytes. Under optimal conditions, the developed TiO2@COF-based SPME-UHPLC-MS/MS method revealed good linearity (R2 ≥ 0.997) with LODs ranging from 0.05 to 0.38 ng/mL for PLs, the extraction recoveries and matrix effects ranging from 83.09-112.03% and 85.38-113.67%, respectively. As a high-throughput pretreatment method, satisfactory probe-to-probe reproducibility rates of 2.7-10.1% were obtained. Finally, the TiO2@COF-based SPME-UHPLC-MS/MS method was applied to analyze LPC 14:0, LPC 16:0, LPC 18:0, LPC 18:1, LPC 19:0, PC 16:0/18:1, and PC 18:0 in serum samples from early LC patients (n = 15), early TC patients (n = 15), and healthy volunteers (n = 15). The results indicated that cancer patients could be effectively differentiated from healthy controls using orthogonal partial least squares discriminant analysis (OPLS-DA). In conclusion, the established TiO2@COF-based SPME-UHPLC-MS/MS method is reliable for the rapid determination of the seven PLs in serum samples, which is promising for early diagnosis of head and neck cancers.

Plasma lipidomic profiling of thiopurine-induced leukopenia after NUDT15 genotype-guided dosing in Chinese IBD patients

Introduction

Thiopurines, azathiopurine (AZA) and mercaptopurine (6-MP) have been regularly used in the treatment of inflammatory bowel disease (IBD). Despite optimized dosage adjustment based on the NUDT15 genotypes, some patients still discontinue or change treatment regimens due to thiopurine-induced leukopenia.

Methods

We proposed a prospective observational study of lipidomics to reveal the lipids perturbations associated with thiopurine-induced leukopenia. One hundred and twenty-seven IBD participants treated with thiopurine were enrolled, twenty-seven of which have developed thiopurine-induced leucopenia. Plasma lipid profiles were measured using Ultra-High-Performance Liquid Chromatography-Tandem Q-Exactive. Lipidomic alterations were validated with an independent validation cohort (leukopenia n = 26, non-leukopenia n = 74).

Results

Using univariate and multivariate analysis, there were 16 lipid species from four lipid classes, triglyceride (n = 11), sphingomyelin (n = 1), phosphatidylcholine (n = 1) and lactosylceramide (n = 3) identified. Based on machine learning feature reduction and variable screening strategies, the random forest algorithm established by six lipids showed an excellent performance to distinguish the leukopenia group from the normal group, with a model accuracy of 95.28% (discovery cohort), 79.00% (validation cohort) and an area under the receiver operating characteristic (ROC) curve (ROC-AUC) of 0.9989 (discovery cohort), 0.8098 (validation cohort).

Discussion

Our novel findings suggested that lipidomic provided unique insights into formulating individualized medication strategies for thiopurines in IBD patients.

A rapid single-phase extraction for polar staphylococcal lipids

The lipid membrane is gaining appreciation as a critical factor in the emergence of antibiotic resistance, both for antibiotics that target lipid synthesis or the membrane directly and for cell-wall-targeting antibiotics. The methods used to study the emergence of antibiotic resistance in vitro can generate a large number of samples that may be low in volume and in cell density. As in eukaryotic/mammalian lipidomics, two-phase liquid-liquid extractions are the most commonly used approach to recover lipids from bacteria. The need to separate the lipid layer is cumbersome for high-throughput applications and can be a source of poor reproducibility or contaminant introduction. While several single-phase extractions have been proposed for serum, tissue, and eukaryotic cells, there have been far fewer efforts to adapt or develop such methods for bacteria lipidomics. Here, we describe a simple, single-phase lipid extraction method based on methanol, acetonitrile, and water-the MAW method. The merits of the MAW method are evaluated against the Bligh & Dyer (B&D) method for the recovery of the major membrane lipids (phosphatidylglycerols, diglycosyldiacylglycerols, and lysyl-phosphatidylglycerols) in the Gram-positive pathogen Staphylococcus aureus. We demonstrate that the MAW method achieves recoveries that are comparable to that of the B&D extraction (≥ 85% for PG 15:0/d₇-18:1). The benefits of the MAW method enable the detection of lipids from lower amounts of bacteria than the B&D method (0.57 vs 0.74 McFarlands for PG 32:0, respectively) and is easily scaled down to microplate volumes to facilitate high-throughput studies of bacterial lipids.

Direct Coupling of SPME to Mass Spectrometry

Solid-phase microextraction devices are normally analyzed by gas or liquid chromatography. Their use has become increasingly widespread since their introduction in 1990, and nowadays most analytical laboratories use or have used SPME as an efficient and green method to perform analyte extraction and sample clean-up in one step. The SPME technique is intrinsically flexible, and allows for a high degree of optimization with regard to the extracting phase, as well as the way sample is analyzed. Since its introduction, researchers have been trying different ways to transfer analytes extracted from the solid phase to a mass spectrometer, with the aim to increase throughput and reduce solvent, gas usage and costs associated with conventional chromatographic techniques. Furthermore, but not less important, for pure fun of developing new, more efficient and sensitive analytical strategies! This chapter aims at providing a comprehensive overview of the most relevant non-chromatographic mass spectrometric approaches developed for SPME. Technical aspects of each SPME-MS approach will be discussed, highlighting their advantages, disadvantages and future potential developments. Particular emphasis will be given on the most recent direct coupling approaches using novel ionization approaches, and a concise overview of the existing applications will also be provided.

Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer

Cis-diol metabolic reprogramming evolves during primary liver cancer (PLC) initiation and progression. However, owing to the low concentrations and highly structural heterogeneity of cis-diols in vivo, severe interference from complex biofluids and limited profiling coverage of existing methods, in-depth profiling of cis-diol metabolites and linking their specific changes with PLC remain challenging. Besides, due to the low specificity of widely used protein biomarkers, accurate classification of PLC from hepatitis still represents an unmet need in clinical diagnostics. Herein, to high-coverage profile cis-diols and explore the translational potential of them as biomarkers, a machine learning-empowered boronate affinity extraction-solvent evaporation assisted enrichment-mass spectrometry (MLE-BESE-MS) was developed. A single analytical platform integrated with multiple complementary functions, including pH-controlled boronate affinity extraction, solvent evaporation-assisted enrichment and nanoelectrospray ionization-based cis-diol identification, was constructed, which significantly improved the metabolite coverage. Meanwhile, by virtue of machine learning (principal components analysis, orthogonal partial least-squares discrimination analysis and random forest), collected cis-diols were statistically screened to extract efficient features for precise PLC diagnosis, and the results outperform the routinely used protein biomarker-based methods both in sensitivity (87.5% vs. less than 70%) and specificity (85.7% vs. ca. 80%). This machine learning-empowered integrated MS platform advanced the targeted metabolic analysis for early cancer diagnosis, rendering great promise for clinical translation.

Solid Phase Microextraction—A Promising Tool for Graft Quality Monitoring in Solid Organ Transplantation

Solid organ transplantation is a life-saving intervention for patients suffering from end-stage organ failure. Although improvements in surgical techniques, standards of care, and immunosuppression have been observed over the last few decades, transplant centers have to face the problem of an insufficient number of organs for transplantation concerning the growing demand. An opportunity to increase the pool of organs intended for transplantation is the more frequent use of organs from extended criteria and the development of analytical methods allowing for a better assessment of the quality of organs to minimize the risk of post-transplant organ injury and rejection. Therefore, solid-phase microextraction (SPME) has been proposed in various studies as an effective tool for determining compounds of significance during graft function assessment or for the chemical profiling of grafts undergoing various preservation protocols. This review summarizes how SPME addresses the analytical challenges associated with different matrices utilized in the peri-transplant period and discusses its potential as a diagnostic tool in future work.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

Innovative Application of Metabolomics on Bioactive Ingredients of Foods

Metabolomics, as a new omics technology, has been widely accepted by researchers and has shown great potential in the field of nutrition and health in recent years. This review briefly introduces the process of metabolomics analysis, including sample preparation and extraction, derivatization, separation and detection, and data processing. This paper focuses on the application of metabolomics in food-derived bioactive ingredients. For example, metabolomics techniques are used to analyze metabolites in food to find bioactive substances or new metabolites in food materials. Moreover, bioactive substances have been tested in vitro and in vivo, as well as in humans, to investigate the changes of metabolites and the underlying metabolic pathways, among which metabolomics is used to find potential biomarkers and targets. Metabolomics provides a new approach for the prevention and regulation of chronic diseases and the study of the underlying mechanisms. It also provides strong support for the development of functional food or drugs. Although metabolomics has some limitations such as low sensitivity, poor repeatability, and limited detection range, it is developing rapidly in general, and also in the field of nutrition and health. At the end of this paper, we put forward our own insights on the development prospects of metabolomics in the application of bioactive ingredients in food.

A Direct Infusion Probe for Rapid Metabolomics of Low-Volume Samples

Targeted and nontargeted metabolomics has the potential to evaluate and detect global metabolite changes in biological systems. Direct infusion mass spectrometric analysis enables detection of all ionizable small molecules, thus simultaneously providing information on both metabolites and lipids in chemically complex samples. However, to unravel the heterogeneity of the metabolic status of cells in culture and tissue a low number of cells per sample should be analyzed with high sensitivity, which requires low sample volumes. Here, we present the design and characterization of the direct infusion probe, DIP. The DIP is simple to build and position directly in front of a mass spectrometer for rapid metabolomics of chemically complex biological samples using pneumatically assisted electrospray ionization at 1 μL/min flow rate. The resulting data is acquired in a square wave profile with minimal carryover between samples that enhances throughput and enables several minutes of uniform MS signal from 5 μL sample volumes. The DIP was applied to study the intracellular metabolism of insulin secreting INS-1 cells and the results show that exposure to 20 mM glucose for 15 min significantly alters the abundance of several small metabolites, amino acids, and lipids.

The metabolic fate of oxaliplatin in the biological milieu investigated during in vivo lung perfusion using a unique miniaturized sampling approach based on solid-phase microextraction coupled with liquid chromatography-mass spectrometry

Adjuvant chemotherapy after pulmonary metastasectomy for colorectal cancer may reduce recurrence and improve survival rates; however, the benefits of this treatment are limited by the significant side effects that accompany it. The development of a novel in vivo lung perfusion (IVLP) platform would permit the localized delivery of high doses of chemotherapeutic drugs to target residual micrometastatic disease. Nonetheless, it is critical to continuously monitor the levels of such drugs during IVLP administration, as lung injury can occur if tissue concentrations are not maintained within the therapeutic window. This paper presents a simple chemical-biopsy approach based on sampling with a small nitinol wire coated with a sorbent of biocompatible morphology and evaluates its applicability for the near-real-time in vivo determination of oxaliplatin (OxPt) in a 72-h porcine IVLP survival model. To this end, the pigs underwent a 3-h left lung IVLP with 3 doses of the tested drug (5, 7.5, and 40 mg/L), which were administered to the perfusion circuit reservoir as a bolus after a full perfusion flow had been established. Along with OxPt levels, the biocompatible solid-phase microextraction (SPME) probes were employed to profile other low-molecular-weight compounds to provide spatial and temporal information about the toxicity of chemotherapy or lung injury. The resultant measurements revealed a rather heterogeneous distribution of OxPt (over the course of IVLP) in the two sampled sections of the lung. In most cases, the OxPt concentration in the lung tissue peaked during the second hour of IVLP, with this trend being more evident in the upper section. In turn, OxPt in supernatant samples represented ∼25% of the entire drug after the first hour of perfusion, which may be attributable to the binding of OxPt to albumin, its sequestration into erythrocytes, or its rapid nonenzymatic biotransformation. Additionally, the Bio-SPME probes also facilitated the extraction of various endogenous molecules for the purpose of screening biochemical pathways affected during IVLP (i.e., lipid and amino acid metabolism, steroidogenesis, or purine metabolism). Overall, the results of this study demonstrate that the minimally invasive SPME-based sampling approach presented in this work can serve as (pre)clinical and precise bedside medical tool.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

Dynamic Metabolic Changes During Prolonged Ex Situ Heart Perfusion Are Associated With Myocardial Functional Decline

Ex situ heart perfusion (ESHP) was developed to preserve and evaluate donated hearts in a perfused beating state. However, myocardial function declines during ESHP, which limits the duration of perfusion and the potential to expand the donor pool. In this research, we combine a novel, minimally-invasive sampling approach with comparative global metabolite profiling to evaluate changes in the metabolomic patterns associated with declines in myocardial function during ESHP. Biocompatible solid-phase microextraction (SPME) microprobes serving as chemical biopsy were used to sample heart tissue and perfusate in a translational porcine ESHP model and a small cohort of clinical cases. In addition, six core-needle biopsies of the left ventricular wall were collected to compare the performance of our SPME sampling method against that of traditional tissue-collection. Our state-of-the-art metabolomics platform allowed us to identify a large number of significantly altered metabolites and lipid species that presented comparable profile of alterations to conventional biopsies. However, significant discrepancies in the pool of identified analytes using two sampling methods (SPME vs. biopsy) were also identified concerning mainly compounds susceptible to dynamic biotransformation and most likely being a result of low-invasive nature of SPME. Overall, our results revealed striking metabolic alterations during prolonged 8h-ESHP associated with uncontrolled inflammation not counterbalanced by resolution, endothelial injury, accelerated mitochondrial oxidative stress, the disruption of mitochondrial bioenergetics, and the accumulation of harmful lipid species. In conclusion, the combination of perfusion parameters and metabolomics can uncover various mechanisms of organ injury and recovery, which can help differentiate between donor hearts that are transplantable from those that should be discarded.

Metabolomic fingerprinting of porcine lung tissue during pre-clinical prolonged ex vivo lung perfusion using in vivo SPME coupled with LC-HRMS

Normothermic ex vivo lung perfusion (NEVLP) has emerged as a modernized organ preservation technique that allows for detailed assessment of donor lung function prior to transplantation. The main goal of this study was to identify potential biomarkers of lung function and/or injury during a prolonged (19 h) NEVLP procedure using in vivo solid-phase microextraction (SPME) technology followed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). The use of minimally invasive in vivo SPME fibers for repeated sampling of biological tissue permits the monitoring and evaluation of biochemical changes and alterations in the metabolomic profile of the lung. These in vivo SPME fibers were directly introduced into the lung and were also used to extract metabolites (on-site SPME) from fresh perfusate samples collected alongside lung samplings. A subsequent goal of the study was to assess the feasibility of SPME as an in vivo method in metabolomics studies, in comparison to the traditional in-lab metabolomics workflow. Several upregulated biochemical pathways involved in pro- and anti-inflammatory responses, as well as lipid metabolism, were observed during extended lung perfusion, especially between the 11th and 12th hours of the procedure, in both lung and perfusate samples. However, several unstable and/or short-lived metabolites, such as neuroprostanes, have been extracted from lung tissue in vivo using SPME fibers. On-site monitoring of the metabolomic profiles of both lung tissues through in vivo SPME and perfusate samples on site throughout the prolonged NEVLP procedure can be effectively performed using in vivo SPME technology.

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In vivo SPME monitors metabolic changes in porcine lung during 19-h NEVLP.

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On-site SPME for perfusate sampling monitors metabolite composition during NEVLP.

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SPME-LC-HRMS permits identification of potential metabolic markers of lung function.

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Stored perfusate provides less relevant metabolome information compared to on-site perfusate samples.

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In vivo SPME of the lung provides more metabolomic information than perfusate sampling.

Enantioselective metabolomics by liquid chromatography-mass spectrometry

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

Controllable in situ growth of novel octahedral TiO2 nanoparticles on nickel/titanium alloy fiber substrate for selective solid-phase microextraction of ultraviolet filters in water samples

The nature and fabrication of fiber coatings with good adsorption capacity and selectivity play a decisive role in solid-phase microextraction (SPME). In this work, a novel SPME fiber was fabricated through hydrothermal in situ growth of octahedral TiO₂ nanoparticles (TiO₂NPs) on a superelastic nickel/titanium alloy (NiTi) wire substrate in acid solution. The resulting fiber coatings were characterized by scanning electron microscopy and energy dispersive X-ray spectroscopy. Acid types, acid concentration as well as hydrothermal temperature and time were found to be effective route to manipulate the morphologies and composition of TiO₂-based nanoflakes grown on the NiTi fiber substrates. At the concentration of 0.4 mol L⁻¹ HCl as well as hydrothermal temperature of 150 °C and hydrothermal time of 12 h, TiO₂NPs were in situ grown on the NiTi wire substrates. The obtained NiTi wire with the TiO₂NPs coating (NiTi@TiO₂NPs fiber) was employed to investigate the adsorption of some representative aromatic analytes in water samples coupling with high-performance liquid chromatography with UV detection (HPLC/UV). The results clearly demonstrate that the fiber exhibits good extraction selectivity for ultraviolet filters (UVFs). In view of good extraction selectivity for the selected UVFs, the key experimental parameters were optimized. Under the optimum conditions, the calibration curves were linear in the ranges of 0.05–100 μg L⁻¹ with the correlation coefficients greater than 0.998. Limits of detection (LODs) were 0.007 to 0.064 μg L⁻¹. Furthermore, the intra-day and inter-day repeatability of the proposed method with the single fiber varied from 4.3% to 6.1% and from 4.5% to 6.8%, respectively. The fiber-to-fiber reproducibility ranged from 5.8% to 8.2%. The developed SPME-HPLC/UV method was applied to selective preconcentration and sensitive determination of target UVFs from real water samples. Moreover, the fabricated fiber showed precisely controllable growth and 150 extraction and desorption cycles.

This work presents a facile strategy with in situ growth of TiO₂ nanoparticles on nickel/titanium alloy wire through hydrothermal method for selective preconcentration and determination of UVFs in water.

Novel solid-phase microextraction fiber coatings: A review

The materials used for the fabrication of solid-phase microextraction fiber coatings in the past five years are summarized in the current review, including carbon, metal-organic frameworks, covalent organic frameworks, aerogel, polymer, ionic liquids/poly (ionic liquids), metal oxides, and natural materials. The preparation approaches of different coatings, such as sol-gel technique, in-situ growth, electrodeposition, and glue methods, are briefly reviewed together with the evolution of the supporting substrates. In addition, the limitations of the current coatings and the future development directions of solid-phase microextraction are presented.

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.

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.

Ultra-high-performance liquid chromatography high-resolution mass spectrometry variants for metabolomics research

Ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) variants currently represent the best tools to tackle the challenges of complexity and lack of comprehensive coverage of the metabolome. UHPLC offers flexible and efficient separation coupled with high-sensitivity detection via HRMS, allowing for the detection and identification of a broad range of metabolites. Here we discuss current common strategies for UHPLC-HRMS-based metabolomics, with a focus on expanding metabolome coverage.

Application of an Improved Chloroform-Free Lipid Extraction Method to Staghorn Coral (Acropora cervicornis) Lipidomics Assessments

Lipids are excellent biomarkers for assessing coral stress, although staghorn coral data (Acropora cervicornis) is lacking. Lipid extraction is the most critical step in lipidomic assessments, usually performed using carcinogenic solvents. Efficient alternative using less toxic methods, such as the BUME method using butanol and methanol as extraction solvents, have not been applied to coral lipidomics evaluations. Thus, we aimed to develop a lipidomic approach to identify important coral health biomarkers by comparing different solvent mixtures in staghorn corals. Total lipid extraction was equivalent for both tested methods, but due to its efficiency in extracting polar lipids, the BUME method was chosen. It was then applied to different coral masses (0.33-1.00 g), resulting in non-significant differences concerning number of lipid classes and compounds. Therefore, this method can be successfully applied to coral assessments in a climate change context, with the added benefit of low sample masses, lessening coral sampling impacts.

Serum metabolic fingerprinting of psoriasis and psoriatic arthritis patients using solid-phase microextraction-liquid chromatography-high-resolution mass spectrometry

INTRODUCTION

Psoriatic arthritis (PsA), an inflammatory arthritis that develops in individuals with psoriasis, is associated with reduced quality of life. Identifying biomarkers associated with development of PsA as well as with PsA disease activity may help management of psoriatic disease.

OBJECTIVES

To use metabolomic fingerprinting to determine potential candidate markers of disease conversion (psoriasis to PsA) and/or PsA activity.

METHODS

A novel sample preparation protocol based on solid-phase microextraction (SPME) was used to prepare serum samples obtained from: (1) individuals with psoriasis, some of whom develop psoriatic arthritis (n = 20); (2) individuals with varying PsA activity (mild, moderate, severe; n = 10 each) and (3) healthy controls (n = 10). Metabolomic fingerprinting of the obtained extracts was performed using reversed-phase liquid chromatography coupled to high resolution mass spectrometry.

RESULTS

Psoriasis patients who developed PsA had similar metabolomic profiles to patients with mild PsA and were also indistinguishable from patients with psoriasis who did not develop PsA. Elevated levels of selected long-chain fatty acids (e.g., 3-hydroxytetradecanedioic acid) that are associated with dysregulation of fatty acid metabolism, were observed in patients with severe PsA. In addition, 1,11-undecanedicarboxylic acid-an unusual fatty acid associated with peroxisomal disorders-was also identified as a classifier in PsA patients vs. healthy individuals. Furthermore, a number of different eicosanoids with either pro- or anti-inflammatory properties were detected solely in serum samples of patients with moderate and severe PsA.

CONCLUSION

A global metabolomics approach was employed to analyze the serum metabolome of patients with psoriasis, PsA, and healthy controls in order to examine potential differences in the biochemical profiles at a metabolite level. A closer examination of circulating metabolites may potentially provide markers of PsA activity.

Review: Metabolomics as a prediction tool for plants performance under environmental stress

Metabolomics as a diagnosis tool for plant performance has shown good features for breeding and crop improvement. Additionally, due to limitations in land area and the increasing climate changes, breeding projects focusing on abiotic stress tolerance are becoming essential. Nowadays no universal method is available to identify predictive metabolic markers. As a result, research aims must dictate the best method or combination of methods. To this end, we will introduce the key aspects to consider regarding growth scenarios and sampling strategies and discuss major analytical and data treatment approaches that are available to find metabolic markers of plant performance.

Assessment of solid phase microextraction as a sample preparation tool for untargeted analysis of brain tissue using liquid chromatography-mass spectrometry

This work presents an evaluation of solid-phase microextraction (SPME) SPME in combination with liquid chromatography-high resolution mass spectrometry (LC-HRMS) as an analytical approach for untargeted brain analysis. The study included a characterization of the metabolite coverage provided by C18, mixed-mode (MM, with benzene sulfonic acid and C18 functionalities), and hydrophilic lipophilic balanced (HLB) particles as sorbents in SPME coatings after extraction from cow brain homogenate at static conditions. The effects of desorption solvent, extraction time, and chromatographic modes on the metabolite features detected were investigated. Method precision and absolute matrix effects were also assessed. Among the main findings of this work, it was observed that all three tested coating chemistries were able to provide comparable brain tissue information. HLB provided higher responses for polar metabolites; however, as these fibers were prepared in-house, higher inter-fiber relative standard deviations were also observed. C18 and HLB coatings offered similar responses with respect to lipid-related features, whereas MM and C18 provided the best results in terms of method precision. Our results also showed that the use of methanol is essential for effective desorption of non-polar metabolites. Using a reversed-phase chromatographic method, an average of 800 and 1200 brain metabolite features detected in positive and negative modes, respectively, met inter-fibre RSD values below 30% (n=4) after removal of fibre and solvent artefacts from the associated datasets. For features detected using a lipidomics method, a total of 900 and 1800 features detected using C18 fibers in positive and negative mode, respectively, met the same criteria. In terms of absolute matrix effects, the majority of the model metabolites tested showed values between 80 and 120%, which are within the acceptable range. Overall, the findings of this work lay the foundation for further optimization of parameters for SPME-LC-HRMS methods suitable for in vivo and ex vivo brain (and other tissue) untargeted studies, and support the applicability of this approach for non-destructive tissue metabolomics.

An Overview on Truffle Aroma and Main Volatile Compounds

Truffles are underground edible fungi that grow symbiotically with plant roots. They have been globally considered as one of the most expensive foods because of their rarity, unique aroma, and high nutritional value as antioxidant, anti-inflammatory, antiviral, hepatoprotective, anti-mutagenic, antituberculoid immunomodulatory, antitumor, antimicrobial, and aphrodisiac. The unique flavor and fragrance of truffles is one of the main reasons to get worldwide attraction as a food product. So, the aim of this review was to summarize the relevant literature with particular attention to the active aroma components as well as the various sample preparation and analytical techniques used to identify them. The major analytical methods used for the determination of volatile organic compounds (VOC) in truffles are gas chromatography (GC), proton-transfer-reaction mass spectrometry (PTR-MS), and electronic nose sensing (EN). In addition, factors influencing truffle aroma are also highlighted. For this reason, this review can be considered a good reference for research concerning aroma profiles of different species of truffles to deepen the knowledge about a complex odor of various truffles.

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

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

Recent advances in the application of metabolomics for food safety control and food quality analyses

As one of the omics fields, metabolomics has unique advantages in facilitating the understanding of physiological and pathological activities in biology, physiology, pathology, and food science. In this review, based on developments in analytical chemistry tools, cheminformatics, and bioinformatics methods, we highlight the current applications of metabolomics in food safety, food authenticity and quality, and food traceability. Additionally, the combined use of metabolomics with other omics techniques for "foodomics" is comprehensively described. Finally, the latest developments and advances, practical challenges and limitations, and requirements related to the application of metabolomics are critically discussed, providing new insight into the application of metabolomics in food analysis.

Virgin olive oil metabolomics: A review

Metabolomics involvement in the study of foods is steadily growing. Such a rise is a consequence of the increasing demand in the food sector to address challenges regarding the issues of food safety, quality, and authenticity in a more comprehensive way. Virgin olive oil (VOO) is a key product of the Mediterranean diet, with a globalized consumer interest as it may be associated with various nutritional and health benefits. Despite the strict legislation to protect this high added-value agricultural commodity and offer guarantees to consumers and honest producers, there are still analytical issues needing to be further addressed. Thus, this review aims to present the efforts made using targeted and untargeted metabolomics approaches, namely nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry-based techniques (mainly LC/GC-MS) combined with multivariate statistical analysis. Case-studies focusing on geographical/varietal classification and detection of adulteration are discussed with regards to the identification of possible markers. The advantages and limitations of each of the aforementioned techniques applied to VOO analysis are also highlighted.