Analytical Metabolomics and Applications in Health, Environmental and Food Science

Exploring the potential of high-resolution LC-MS in combination with ion mobility separation and surrogate minimal depth for enhanced almond origin authentication

Almonds (Prunus dulcisMill.) are consumed worldwide and their geographical origin plays a crucial role in determining their market value. In the present study, a total of 250 almond reference samples from six countries (Australia, Spain, Iran, Italy, Morocco, and the USA) were non-polar extracted and analyzed by UPLC-ESI-IM-qToF-MS. Four harvest periods, more than 30 different varieties, including both sweet and bitter almonds, were considered in the method development. Principal component analysis showed that there are three groups of samples with similarities: Australia/USA, Spain/Italy and Iran/Morocco. For origin determination, a random forest achieved an accuracy of 88.8 %. Misclassifications occurred mainly between almonds from the USA and Australia, due to similar varieties and similar external influences such as climate conditions. Metabolites relevant for classification were selected using Surrogate Minimal Depth, with triacylglycerides containing oxidized, odd chained or short chained fatty acids and some phospholipids proven to be the most suitable marker substances. Our results show that focusing on the identified lipids (e. g., using a QqQ-MS instrument) is a promising approach to transfer the origin determination of almonds to routine analysis.

LC-MS/MS-based targeted amino acid metabolic profile of Auricularia cornea grown on pinecone substrate

Pinecone substrate offers an eco-friendly and cost-effective alternative for cultivating edible fungi. This pioneering study explores the 94 amino acids metabolic profiles of Auricularia cornea grown on various pinecone substrates. To our knowledge, this is the first study of quantify A. cornea on an oleaginous substrate (pinecone) using targeted LC-MS /MS-based metabolomics approaches. Five different pinecone substrate percentages (0%, 7%, 14%, 21%, and 28% respectively) were used for A. cornea culture, and the resulting fruiting bodies were analyzed for amino acids metabolic profiles. Detected 79 amino acids metabolites, 15 undetected. High contents of succinic-acid and γ-aminobutyric acid. Thirty-three amino acid metabolites showed significant differences between groups, primarily related to protein synthesis. KEGG analysis revealed that seven major metabolic pathways were significantly enriched. The findings provide valuable insights into the metabolite composition of A. cornea grown on a pinecone substrate, potentially contribute to the understanding of its nutritional and medicinal properties.

Comprehensive Single-Platform Lipidomic/Metabolomic Analysis Using Supercritical Fluid Chromatography-Mass Spectrometry

Supercritical fluid chromatography (SFC) is a rapidly expanding technique in the analysis of nonpolar to moderately polar substances and, more recently, also in the analysis of compounds with higher polarity. Herein, we demonstrate a proof of concept for the application of a commercial SFC instrument with electrospray ionization-mass spectrometry (MS) detection as a platform for the comprehensive analysis of metabolites with the full range of polarities, from nonpolar lipids up to highly polar metabolites. The developed single-platform SFC-MS lipidomic/metabolomic method is based on two consecutive injections of lipid and polar metabolite extracts from biphase methyl tert-butyl ether extraction using a diol column and two different gradient programs of methanol-water-ammonium formate modifier. Detailed development of the method focused mainly on the pressure limits of the system, the long-term repeatability of results, and the chromatographic performance, including optimization of the flow rate program, modifier composition and gradient, and injection solvent selection. The developed method enabled fast and comprehensive analysis of lipids and polar metabolites from plasma within a 24 min cycle with two injections using a simple analytical platform based on a single instrument, column, and mobile phase. Finally, the results from SFC-MS analysis of polar metabolites were compared with widely established liquid chromatography MS analysis in metabolomics. The comparison showed different separation selectivity of metabolites using both methods and overall lower sensitivity of the SFC-MS due to the higher flow rate and worse chromatographic performance.

Characterization and Statistical Optimization of Enterobatin Synthesized by Escherichia coli OQ866153

Microorganisms produce siderophores, which are secondary metabolites with a high affinity for iron. Siderophores have received significant attention due to their diverse applications in ecological and clinical research. In this study, siderophores production by Escherichia coli OQ866153 was optimized using two-stage statistical approach involving Plackett-Burman design (PBD) and response surface methodology (RSM) using central composite design (CCD). Out of 23 variables, succinate, tryptophan, Na2HPO4, CaCl2, agitation, and KH2PO4 were found to have the most significant effect on siderophores production in the first optimization stage with the highest SU% of 43.67%. In the second stage, RSM using CCD was utilized, and the optimal conditions were determined to be 0.3 g/l succinate, 0 g/l tryptophan, 6 g/l Na2HPO4, 0.1 g/l CaCl2, 150 RPM agitation, and 0.6 g/l KH2PO4, resulting in a maximum siderophore units (SU%) of 89.13%. The model was significant, as indicated by the model f-value of 314.14 (p-value = 0.0004) and coefficient of determination R2 of 0.9950. During validation experiments, the obtained maximum SU% was increased up to 87.1472%, which was two times as the value obtained under ordinary conditions (46.62%). The produced siderophores were purified and characterized using 1H, 13C NMR, IR spectroscopy. The obtained results indicated that the compound was enterobactin and entABCDEF genes were further detected in Escherichia coli OQ866153 extracted DNA. To our knowledge, this is the first report of statistical optimization for enterobactin synthesis by an E. coli strain isolated from a clinical source in Egypt.

Pan-Omics in Sheep: Unveiling Genetic Landscapes

Multi-omics-integrated analysis, known as panomics, represents an advanced methodology that harnesses various high-throughput technologies encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Sheep, playing a pivotal role in agricultural sectors due to their substantial economic importance, have witnessed remarkable advancements in genetic breeding through the amalgamation of multiomics analyses, particularly with the evolution of high-throughput technologies. This integrative approach has established a robust theoretical foundation, enabling a deeper understanding of sheep genetics and fostering improvements in breeding strategies. The comprehensive insights obtained through this approach shed light on diverse facets of sheep development, including growth, reproduction, disease resistance, and the quality of livestock products. This review primarily focuses on the application of principal omics analysis technologies in sheep, emphasizing correlation studies between multiomics data and specific traits such as meat quality, wool characteristics, and reproductive features. Additionally, this paper anticipates forthcoming trends and potential developments in this field.

Soluble sugar and organic acid composition and flavor evaluation of Chinese cherry fruits

Chinese cherry is an economically important fruit crop native to China. Flavor quality is greatly influenced by compositions of soluble sugars and organic acids. To better understand the flavor quality of Chinese cherry, we determined sugar and acid components in thirty-eight landrace and cultivar collections, and two wild resources using the HPLC method. Glucose and fructose were the main components, accounting for 85.91% of soluble sugars. Malic acid was the predominant organic acid, with an average proportion of 65.73% of total acids. Correlation and PCA analysis revealed seven key indicators for evaluating fruit flavor. Compared with wild Chinese cherry, the cultivated collections exhibited higher levels of soluble sugars, especially fructose, and lower levels of organic acid, particularly malic acid in fruits. Finally, we have established grading criteria for seven flavor indicators in Chinese cherry. Our study provides valuable references for identifying flavor compounds and improving flavor quality of Chinese cherry.

Nondestructive Metabolomic Fingerprinting: FTIR, NIR and Raman Spectroscopy in Food Screening

In recent years, there has been renewed interest in the maintenance of food quality and food safety on the basis of metabolomic fingerprinting using vibrational spectroscopy combined with multivariate chemometrics. Nontargeted spectroscopy techniques such as FTIR, NIR and Raman can provide fingerprint information for metabolomic constituents in agricultural products, natural products and foods in a high-throughput, cost-effective and rapid way. In the current review, we tried to explain the capabilities of FTIR, NIR and Raman spectroscopy techniques combined with multivariate analysis for metabolic fingerprinting and profiling. Previous contributions highlighted the considerable potential of these analytical techniques for the detection and quantification of key constituents, such as aromatic amino acids, peptides, aromatic acids, carotenoids, alcohols, terpenoids and flavonoids in the food matrices. Additionally, promising results were obtained for the identification and characterization of different microorganism species such as fungus, bacterial strains and yeasts using these techniques combined with supervised and unsupervised pattern recognition techniques. In conclusion, this review summarized the cutting-edge applications of FTIR, NIR and Raman spectroscopy techniques equipped with multivariate statistics for food analysis and foodomics in the context of metabolomic fingerprinting and profiling.

Exploring Human Metabolome after Wine Intake-A Review

Wine has a rich history dating back to 2200 BC, originally recognized for its medicinal properties. Today, with the aid of advanced technologies like metabolomics and sophisticated analytical techniques, we have gained remarkable insights into the molecular-level changes induced by wine consumption in the human organism. This review embarks on a comprehensive exploration of the alterations in human metabolome associated with wine consumption. A great number of 51 studies from the last 25 years were reviewed; these studies systematically investigated shifts in metabolic profiles within blood, urine, and feces samples, encompassing both short-term and long-term studies of the consumption of wine and wine derivatives. Significant metabolic alterations were observed in a wide variety of metabolites belonging to different compound classes, such as phenolic compounds, lipids, organic acids, and amino acids, among others. Within these classes, both endogenous metabolites as well as diet-related metabolites that exhibited up-regulation or down-regulation following wine consumption were included. The up-regulation of short-chain fatty acids and the down-regulation of sphingomyelins after wine intake, as well as the up-regulation of gut microbial fermentation metabolites like vanillic and syringic acid are some of the most important findings reported in the reviewed literature. Our results confirm the intact passage of certain wine compounds, such as tartaric acid and other wine acids, to the human organism. In an era where the health effects of wine consumption are of growing interest, this review offers a holistic perspective on the metabolic underpinnings of this centuries-old tradition.

Recent advances in the combination of organic solvent-free extraction, chemical standardization, antioxidant assay, and cell culture metabolomics for functional food and its by-product

Functional foods and their by-products contain a wide range of bioactive components with an array of health benefits and were proposed to improve public health, well-being, and others. To achieve a circular economy, the processing and extraction of flavonoids, phenolic compounds, and others from functional food and agri-food wastes will require the use of environmentally friendly, sustainable, and a low-cost solution. Extraction methods that can eliminate the use of organic solvents, suitable for use in the laboratory and production of extracts will be covered. This will include subcritical water extraction (SBE), pressurized hot water extraction (PHWE), supercritical fluid extraction (SFE), and others. Based on the selected analytical methods, the determination of the marker or bioactive compounds and chemical fingerprints will provide the control measures to identify the batch-to-batch variation of the composition of the functional food products obtained. The combination of chemical standardization with antioxidant assay, such as DPPH and ABTS+ will provide further information on the quality of the extracts. Lastly, to ascertain the biological and physiological relevance of the antioxidant properties of the target sample, treatment of the antioxidant compounds or extracts was carried out using cellular models, and validated using other experimental endpoints, such as metabolomics.

Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry

Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.

Applications of multi-omics techniques to unravel the fermentation process and the flavor formation mechanism in fermented foods

Fermented foods are important components of the human diet. There is increasing awareness of abundant nutritional and functional properties present in fermented foods that arise from the transformation of substrates by microbial communities. Thus, it is significant to unravel the microbial communities and mechanisms of characteristic flavor formation occurring during fermentation. There has been rapid development of high-throughput and other omics technologies, such as metaproteomics and metabolomics, and as a result, there is growing recognition of the importance of integrating these approaches. The successful applications of multi-omics approaches and bioinformatics analyses have provided a solid foundation for exploring the fermentation process. Compared with single-omics, multi-omics analyses more accurately delineate microbial and molecular features, thus they are more apt to reveal the mechanisms of fermentation. This review introduces fermented foods and an overview of single-omics technologies - including metagenomics, metatranscriptomics, metaproteomics, and metabolomics. We also discuss integrated multi-omics and bioinformatic analyses and their role in recent research progress related to fermented foods, as well as summarize the main potential pathways involved in certain fermented foods. In the future, multilayered analyses of multi-omics data should be conducted to enable better understanding of flavor formation mechanisms in fermented foods.

Filling gaps in animal welfare assessment through metabolomics

Sustainability has become a central issue in Italian livestock systems driving food business operators to adopt high standards of production concerning animal husbandry conditions. Meat sector is largely involved in this ecological transition with the introduction of new label claims concerning the defense of animal welfare (AW). These new guarantees referred to AW provision require new tools for the purpose of authenticity and traceability to assure meat supply chain integrity. Over the years, European Union (EU) Regulations, national, and international initiatives proposed provisions and guidelines for assuring AW introducing requirements to be complied with and providing tools based on scoring systems for a proper animal status assessment. However, the comprehensive and objective assessment of the AW status remains challenging. In this regard, phenotypic insights at molecular level may be investigated by metabolomics, one of the most recent high-throughput omics techniques. Recent advances in analytical and bioinformatic technologies have led to the identification of relevant biomarkers involved in complex clinical phenotypes of diverse biological systems suggesting that metabolomics is a key tool for biomarker discovery. In the present review, the Five Domains model has been employed as a vademecum describing AW. Starting from the individual Domains-nutrition (I), environment (II), health (III), behavior (IV), and mental state (V)-applications and advances of metabolomics related to AW setting aimed at investigating phenotypic outcomes on molecular scale and elucidating the biological routes most perturbed from external solicitations, are reviewed. Strengths and weaknesses of the current state-of-art are highlighted, and new frontiers to be explored for AW assessment throughout the metabolomics approach are argued. Moreover, a detailed description of metabolomics workflow is provided to understand dos and don'ts at experimental level to pursue effective results. Combining the demand for new assessment tools and meat market trends, a new cross-strategy is proposed as the promising combo for the future of AW assessment.

Understanding the Seasonal Effect of Metabolite Production in Terminalia catappa L. Leaves through a Concatenated MS- and NMR-Based Metabolomics Approach

Terminalia catappa L. (Combretaceae) is a medicinal plant that is part of the Brazilian biodiversity; this plant is popularly used for the treatment of a wide range of diseases. To better understand the chemical composition of T. catappa in different seasons, we conducted a thorough study using LC-MS and NMR data analysis techniques. The study helped obtain a chemical profile of the plant ethanolic extracts in different seasons of the year (spring, summer, autumn, and winter). The dereplication of LC-HRMS data allowed the annotation of 90 compounds in the extracts of T. catappa (hydrolyzable tannins, ellagic acid derivatives, and glycosylated flavonoids). Triterpenes and C-glycosyl flavones were the compounds that significantly contributed to differences observed between T. catappa plant samples harvested in autumn/winter and spring, respectively. The variations observed in the compound composition of the plant leaves may be related to processes induced by environmental stress and leaf development. Data fusion applied in the metabolomic profiling study allowed us to identify metabolites with greater confidence, and provided a better understanding regarding the production of specialized metabolites in T. catappa leaves under different environmental conditions, which may be useful to establish appropriate quality criteria for the standardization of this medicinal plant.

Metabolomics-Based Mechanistic Insights into Revealing the Adverse Effects of Pesticides on Plants: An Interactive Review

In plant biology, metabolomics is often used to quantitatively assess small molecules, metabolites, and their intermediates in plants. Metabolomics has frequently been applied to detect metabolic alterations in plants exposed to various biotic and abiotic stresses, including pesticides. The widespread use of pesticides and agrochemicals in intensive crop production systems is a serious threat to the functionality and sustainability of agroecosystems. Pesticide accumulation in soil may disrupt soil-plant relationships, thereby posing a pollution risk to agricultural output. Application of metabolomic techniques in the assessment of the biological consequences of pesticides at the molecular level has emerged as a crucial technique in exposome investigations. State-of-the-art metabolomic approaches such as GC-MS, LC-MS/MS UHPLC, UPLC-IMS-QToF, GC/EI/MS, MALDI-TOF MS, and ¹H-HR-MAS NMR, etc., investigating the harmful effects of agricultural pesticides have been reviewed. This updated review seeks to outline the key uses of metabolomics related to the evaluation of the toxicological impacts of pesticides on agronomically important crops in exposome assays as well as bench-scale studies. Overall, this review describes the potential uses of metabolomics as a method for evaluating the safety of agricultural chemicals for regulatory applications. Additionally, the most recent developments in metabolomic tools applied to pesticide toxicology and also the difficulties in utilizing this approach are discussed.

Integration of LC-MS-Based and GC-MS-Based Metabolic Profiling to Reveal the Effects of Domestication and Boiling on the Composition of Duck Egg Yolks

Egg yolks contain abundant lipids, proteins, and minerals that provide not only essential nutrients for embryonic development but also cheap sources of nutrients for consumers worldwide. Previous composition analyses of egg yolks primarily focused on nutrients such as lipids and minerals. However, few studies have reported the effects of domestication and heating on yolk composition and characteristics. The objective of this study was to investigate the impact of domestication and boiling on the metabolite contents of egg yolks via untargeted metabolomics using GC-MS and LC-MS. In this study, eggs were collected from Fenghua teals, captive mallards, and Shaoxing ducks. Twelve duck eggs (half raw and half cooked) were randomly selected from each variety, and the egg yolks were separated for metabolic profiling. The analysis identified 1205 compounds in the egg yolks. Domestication generated more differential metabolites than boiling, which indicated that the changes in the metabolome of duck egg yolk caused by domestication were greater than those caused by boiling. In a comparative analysis of domestic and mallard ducks, 48 overlapping differential metabolites were discovered. Among them, nine metabolites were upregulated in domesticated ducks, including monoolein, emodin, daidzein, genistein, and glycitein, which may be involved in lipid metabolism; some of them may also act as phytoestrogens (flavonoids). Another 39 metabolites, including imethylethanolamine, harmalan, mannitol, nornicotine, linoleic acid, diphenylamine, proline betaine, alloxanthin, and resolvin d1, were downregulated by domestication and were linked to immunity, anti-inflammatory, antibacterial, and antioxidant properties. Furthermore, four overlapping differential metabolites that included amino acids and dipeptides were discovered in paired comparisons of the raw and boiled samples. Our findings provided new insights into the molecular response of duck domestication and supported the use of metabolomics to examine the impact of boiling on the composition of egg yolks.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

Background

Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people's health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression.

Methodology

We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics.

Results

Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease.

Conclusions

We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

Untargeted metabolomics of the cochleae from two laryngeally echolocating bats

High-frequency hearing is regarded as one of the most functionally important traits in laryngeally echolocating bats. Abundant candidate hearing-related genes have been identified to be the important genetic bases underlying high-frequency hearing for laryngeally echolocating bats, however, extensive metabolites presented in the cochleae have not been studied. In this study, we identified 4,717 annotated metabolites in the cochleae of two typical laryngeally echolocating bats using the liquid chromatography-mass spectroscopy technology, metabolites classified as amino acids, peptides, and fatty acid esters were identified as the most abundant in the cochleae of these two echolocating bat species, Rhinolophus sinicus and Vespertilio sinensis. Furthermore, 357 metabolites were identified as significant differentially accumulated (adjusted p-value <0.05) in the cochleae of these two bat species with distinct echolocating dominant frequencies. Downstream KEGG enrichment analyses indicated that multiple biological processes, including signaling pathways, nervous system, and metabolic process, were putatively different in the cochleae of R. sinicus and V. sinensis. For the first time, this study investigated the extensive metabolites and associated biological pathways in the cochleae of two laryngeal echolocating bats and expanded our knowledge of the metabolic molecular bases underlying high-frequency hearing in the cochleae of echolocating bats.

Hydrophilic Metabolite Composition of Fruiting Bodies and Mycelia of Edible Mushroom Species (Agaricomycetes)

Mushrooms have two components, the fruiting body, which encompasses the stalk and the cap, and the mycelium, which supports the fruiting body underground. The part of the mushroom most commonly consumed is the fruiting body. Given that it is more time consuming to harvest the fruiting body versus simply the mycelia, we were interested in understanding the difference in metabolite content between the fruiting bodies and mycelia of four widely consumed mushrooms in Taiwan: Agrocybe cylindracea (AC), Coprinus comatus (CC), Hericium erinaceus (HE), and Hypsizygus marmoreus (HM). In total, we identified 54 polar metabolites using 1H NMR spectroscopy that included sugar alcohols, amino acids, organic acids, nucleosides and purine/pyrimidine derivatives, sugars, and others. Generally, the fruiting bodies of AC, CC, and HM contained higher amounts of essential amino acids than their corresponding mycelia. Among fruiting bodies, HE had the lowest essential amino acid content. Trehalose was the predominant carbohydrate in most samples except for the mycelia of AC, in which the major sugar was glucose. The amount of adenosine, uridine, and xanthine in the samples was similar, and was higher in fruiting bodies compared with mycelia, except for HM. The organic acid and sugar alcohol content between fruiting bodies and mycelia did not tend to be different. Although each mushroom had a unique metabolic profile, the metabolic profile of fruiting bodies and mycelia were most similar for CC and HE, suggesting that the mycelia of CC and HE may be good replacements for their corresponding fruiting bodies. Additionally, each mushroom species had a unique polar metabolite fingerprint, which could be utilized to identify adulteration.

Absolute Metabolite Quantification Using Pure Shift NMR: Toward Quantitative Metabolic Profiling of Aqueous Biological Samples

Accurate quantification of metabolites by nuclear magnetic resonance (NMR) is of prime importance in the field of health sciences for understanding the metabolic pathways of the investigated system, to address the mechanisms of action of diseases, and improving their diagnosis, treatment, and prognosis. Unfortunately, the absolute quantitative analysis of complex samples is still limited by sensitivity and resolution issues that are intrinsic to this technique. Ultrahigh-resolution pure shift methods have especially shown to be suitable for interpreting mixtures of metabolites in biological samples. Here, we introduce a robust analytical protocol based on the use of a pure shift library of calibration reference spectra to fit the fingerprint of each metabolite of interest and determine its concentration. The approach based on the SAPPHIRE pulse sequence enhanced with a block for solvent suppression has been validated through the results of a series of model mixtures, exhibiting excellent trueness (slope values in the range of 0.93-1.02) and linearity (R² > 0.996) in a total time (a few hours) that is fully compatible with metabolomics studies. Furthermore, we have successfully applied our method to determine the absolute metabolite concentrations in a lymphoma extracellular medium, which improves metabolomic protocols reported to date by providing a quantitative and highly resolved vision of metabolic processes at play.

NMR-based metabolomics reveals tissue metabolic responses to tetramethoxy gossypol in cottonseed oil

BACKGROUND

Cottonseed oil is one of the most widely consumed cooking oils because of its high nutritional benefits and relatively low price. The present study evaluated the effects of tetramethoxy gossypol (TMG), a rarely reported degradation product of free gossypol produced in crudely extracted cottonseed oil, on the metabolic responses of liver, heart, spleen, kidney and lung tissues in rats using proton nuclear magnetic resonance (¹ H NMR) spectroscopy combined with chemometric and bioinformatics techniques.

RESULTS

Endogenous low-molecular-weight metabolites in rat liver, heart, spleen, kidney and lung tissues were profiled by ¹ H NMR spectroscopy. The unsupervised principal components analysis and the supervised orthogonal partial least squares discriminant analysis revealed that the metabolic profiles in liver samples were greatly changed after TMG administration. Twenty significantly changed liver metabolites were screened out and further evaluated by receiver operating characteristic curve analysis, which were closely related to amino acid, glutathione, energy and lipid metabolism.

CONCLUSION

Concerning the potential chronic exposure to TMG in cottonseed oil and other cottonseed products, the cumulative effects of dietary TMG on tissues, especially the liver, should be noted when improving the quality control standard of cottonseed oil. © 2022 Society of Chemical Industry.

Degradation of Xenobiotic Pollutants: An Environmentally Sustainable Approach

The ability of microorganisms to detoxify xenobiotic compounds allows them to thrive in a toxic environment using carbon, phosphorus, sulfur, and nitrogen from the available sources. Biotransformation is the most effective and useful metabolic process to degrade xenobiotic compounds. Microorganisms have an exceptional ability due to particular genes, enzymes, and degradative mechanisms. Microorganisms such as bacteria and fungi have unique properties that enable them to partially or completely metabolize the xenobiotic substances in various ecosystems.There are many cutting-edge approaches available to understand the molecular mechanism of degradative processes and pathways to decontaminate or change the core structure of xenobiotics in nature. These methods examine microorganisms, their metabolic machinery, novel proteins, and catabolic genes. This article addresses recent advances and current trends to characterize the catabolic genes, enzymes and the techniques involved in combating the threat of xenobiotic compounds using an eco-friendly approach.

Old and New Biomarkers Associated with Endothelial Dysfunction in Chronic Hyperglycemia

Chronic hyperglycemia and vascular damage are strictly related. Biomarkers of vascular damage have been intensively studied in the recent years in the quest of reliable cardiovascular risk assessment tools able to facilitate risk stratification and early detection of vascular impairment. The present study is a narrative review with the aim of revising the available evidence on current and novel markers of hyperglycemia-induced vascular damage. After a discussion of classic tools used to investigate endothelial dysfunction, we provide an in-depth description of novel circulating biomarkers (chemokines, extracellular vesicles, and epigenetic and metabolomic biomarkers). Appropriate use of a single as well as a cluster of the discussed biomarkers might enable in a near future (a) the prompt identification of targeted and customized treatment strategies and (b) the follow-up of cardiovascular treatment efficacy over time in clinical research and/or in clinical practice.

Ratiometric Probe for Rapid Naked Eye Detection of Toxic Hydrazine: Real Time Application in Strip Test, Spray Test and Soil Analysis

Striking colorimetric probe (CynH) for abrupt detection of hydrazine under complete aqueous solution was achieved. The water soluble probe was designed with electron "push-pull" strategy by coupling of 4-hydroxy benzaldehyde and 2, 3, 3-trimethylindolinine. The positively charged N-propylated indolinine make the probe completely soluble in water. The probe yields eye catching selective detection of hydrazine over other competing analytes with high sensitivity. Obvious colour change was observed from colourless to appearance of bright pink colour with hydrazine. It reacts quickly with hydrazine within 2 min and makes the probe an effective candidate for practical application. The real time application was demonstrated using paper strip to detect hydrazine vapour. This probe is superior to earlier reported probes because of its effective sensing of hydrazine displayed with various applications including real-time strip based sensing, spray test and soil analysis. In all the examinations, the probe yields distinct response with rapid naked eye colour change which overcomes the drawbacks of previous reports.

CRB-SWATH: A Method for Enhancing Untargeted Precursor Ion Extraction and Automatically Constructing Their Tandem Mass Spectra from SWATH Datasets by Chromatographic Retention Behaviors

Sequential window acquisition of all theoretical spectra (SWATH) as a typical data-independent acquisition (DIA) strategy is favorable for untargeted metabolomics. It could theoretically acquire product ions of all precursor ions, including precursor ions showing chromatographic peaks of rather poor qualities. However, existing data processing methods present limited capabilities in capturing poor-quality peaks of precursor ions. Thus, although their product ions could be acquired, their precursor ions are absent. Here, we present a new strategy, chromatographic retention behavior-SWATH (CRB-SWATH), that could unbiasedly capture poor-quality peaks and provide high resolutions of multiplexed mass spectroscopy (MS/MS) spectra in SWATH datasets. CRB-SWATH monitors CRBs of SWATH-MS signals under a series of altered elution gradients. As signals of compounds differ from noise by showing CRBs, both the precursor and fragment ions are captured, while ignoring their peak qualities. Moreover, CRB-SWATH offers good chances to resolve highly multiplexed MS/MS spectra in SWATH datasets because precursor ions coeluted in a single elution gradient often present different CRBs. In the untargeted metabolic analysis of Hela cell extracts, CRB-SWATH showed the advantage in exclusively capturing 2645 ions of poor-quality peaks (i.e., tiny peaks, discontinuous ion traces, tailing peaks, zigzag peaks, etc.), accounting for 34.4% of all the untargeted precursor ions extracted. Therein, it is noteworthy that among 2116 negative ions detected in hydrophilic interaction liquid chromatography (HILIC) mode, 1284 poor-quality ion peaks (>60%) were exclusively captured by CRB-SWATH. As CRB-SWATH automatically captures a large sum of true ion peaks of poor qualities, extracts MS/MS spectra of high purities, and provides chromatographic retention behaviors of untargeted metabolites for identification and classification, it could be a useful metabolomics tool for understanding biological phenomena better.

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.

Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study

Large-scale untargeted LC-MS-based metabolomic profiling is a valuable source for systems biology and biomarker discovery. Data analysis and processing are major tasks due to the high complexity of generated signals and the presence of unwanted variations. In the present study, we introduce an R-based open-source collection of scripts called OUKS (Omics Untargeted Key Script), which provides comprehensive data processing. OUKS is developed by integrating various R packages and metabolomics software tools and can be easily set up and prepared to create a custom pipeline. Novel computational features are related to quality control samples-based signal processing and are implemented by gradient boosting, tree-based, and other nonlinear regression algorithms. Bladder cancer biomarkers discovery study which is based on untargeted LC-MS profiling of urine samples is performed to demonstrate exhaustive functionality of the developed software tool. Unique examination among dozens of metabolomics-specific data curation methods was carried out at each processing step. As a result, potential biomarkers were identified, statistically validated, and described by metabolism disorders. Our study demonstrates that OUKS helps to make untargeted LC-MS metabolomic profiling with the latest computational features readily accessible in a ready-to-use unified manner to a research community.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.

The Use of Invasive Algae Species as a Source of Secondary Metabolites and Biological Activities: Spain as Case-Study

In the recent decades, algae have proven to be a source of different bioactive compounds with biological activities, which has increased the potential application of these organisms in food, cosmetic, pharmaceutical, animal feed, and other industrial sectors. On the other hand, there is a growing interest in developing effective strategies for control and/or eradication of invasive algae since they have a negative impact on marine ecosystems and in the economy of the affected zones. However, the application of control measures is usually time and resource-consuming and not profitable. Considering this context, the valorization of invasive algae species as a source of bioactive compounds for industrial applications could be a suitable strategy to reduce their population, obtaining both environmental and economic benefits. To carry out this practice, it is necessary to evaluate the chemical and the nutritional composition of the algae as well as the most efficient methods of extracting the compounds of interest. In the case of northwest Spain, five algae species are considered invasive: Asparagopsis armata, Codium fragile, Gracilaria vermiculophylla, Sargassum muticum, and Grateulopia turuturu. This review presents a brief description of their main bioactive compounds, biological activities, and extraction systems employed for their recovery. In addition, evidence of their beneficial properties and the possibility of use them as supplement in diets of aquaculture animals was collected to illustrate one of their possible applications.

State-of-the-Art of Analytical Techniques to Determine Food Fraud in Olive Oils

The benefits of the food industry compared to other sectors are much lower, which is why producers are tempted to commit fraud. Although it is a bad practice committed with a wide variety of foods, it is worth noting the case of olive oil because it is a product of great value and with a high percentage of fraud. It is for all these reasons that the authenticity of olive oil has become a major problem for producers, consumers, and legislators. To avoid such fraud, it is necessary to develop analytical techniques to detect them. In this review, we performed a complete analysis about the available instrumentation used in olive fraud which comprised spectroscopic and spectrometric methodology and analyte separation techniques such as liquid chromatography and gas chromatography. Additionally, other methodology including protein-based biomolecular techniques and analytical approaches like metabolomic, hhyperspectral imaging and chemometrics are discussed.

A Combined Metabolomic and Metagenomic Approach to Discriminate Raw Milk for the Production of Hard Cheese

The chemical composition of milk can be significantly affected by different factors across the dairy supply chain, including primary production practices. Among the latter, the feeding system could drive the nutritional value and technological properties of milk and dairy products. Therefore, in this work, a combined foodomics approach based on both untargeted metabolomics and metagenomics was used to shed light onto the impact of feeding systems (i.e., hay vs. a mixed ration based on hay and fresh forage) on the chemical profile of raw milk for the production of hard cheese. In particular, ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) was used to investigate the chemical profile of raw milk (n = 46) collected from dairy herds located in the Po River Valley (Italy) and considering different feeding systems. Overall, a total of 3320 molecular features were putatively annotated across samples, corresponding to 734 unique compound structures, with significant differences (p < 0.05) between the two feeding regimens under investigation. Additionally, supervised multivariate statistics following metabolomics-based analysis allowed us to clearly discriminate raw milk samples according to the feeding systems, also extrapolating the most discriminant metabolites. Interestingly, 10 compounds were able to strongly explain the differences as imposed by the addition of forage in the cows’ diet, being mainly glycerophospholipids (i.e., lysophosphatidylethanolamines, lysophosphatidylcholines, and phosphatidylcholines), followed by 5-(3′,4′-Dihydroxyphenyl)-gamma-valerolactone-4′-O-glucuronide, 5a-androstan-3a,17b-diol disulfuric acid, and N-stearoyl glycine. The markers identified included both feed-derived (such as phenolic metabolites) and animal-derived compounds (such as lipids and derivatives). Finally, although characterized by a lower prediction ability, the metagenomic profile was found to be significantly correlated to some milk metabolites, with Staphylococcaceae, Pseudomonadaceae, and Dermabacteraceae establishing a higher number of significant correlations with the discriminant metabolites. Therefore, taken together, our preliminary results provide a comprehensive foodomic picture of raw milk samples from different feeding regimens, thus supporting further ad hoc studies investigating the metabolomic and metagenomic changes of milk in all processing conditions.