Chemometrics in metabonomics

Discrimination of beef composition and sensory quality by using rapid Evaporative Ionisation Mass Spectrometry (REIMS)

Herein, we investigated the potential of REIMS analysis for classifying muscle composition and meat sensory quality. The study utilized 116 samples from 29 crossbred Angus × Salers, across three muscle types. Prediction models were developed combining REIMS fingerprints and meat quality metrics. Varying efficacy was observed across REIMS discriminations - muscle type (71 %), marbling level (32 %), untrained consumer evaluated tenderness (36 %), flavor liking (99 %) and juiciness (99 %). Notably, REIMS demonstrated the ability to classify 116 beef across four Meat Standards Australia grades with an overall accuracy of 37 %. Specifically, "premium" beef could be differentiated from "unsatisfactory", "good everyday" and "better than everyday" grades with accuracies of 99 %, 84 %, and 62 %, respectively. Limited efficacy was observed however, in classifying trained panel evaluated sensory quality and fatty acid composition. Additionally, key predictive features were tentatively identified from the REIMS fingerprints primarily comprised of molecular ions present in lipids, phospholipids, and amino acids.

Improving insights from metabolomic functional analysis combining multivariate tools

BACKGROUND

Metabolomics is a scientific field that relies on the comprehensive analysis of metabolites to provide direct insights into functional processes in biological systems. Metabolomic data provides valuable insights into the functional processes of biological systems, often analyzed through univariate and multivariate approaches, and well as with functional or pathway analysis using different methods such as mummichog. Yet, the integration of results from these sources to aid the interpretation of their biological significance remains challenging. This represents a significant bottleneck limiting the applicability of multivariate analysis of metabolomic data, despite its potential for providing deep biological insights.

RESULTS

In this work we propose two straightforward methods to facilitate the interpretation of results from multivariate analysis and functional metabolic analysis using: i) p-values from multivariate tests as input in functional analysis, and ii) cluster-CV to assess the impact on the predictive performance of a multivariate model at the pathway level. Four simulated data sets were analyzed including a data set with no class separation, and three data sets with a statistically significant discrimination between classes by including either univariate, multivariate, or both types of discriminant effects. The data sets were analyzed using univariate tests and OPLS-DA. Furthermore, p-values for each feature estimated by univariate analysis and OPLS-DA were used as input for functional analysis in mummichog. Cluster-CV was then used to assess the effect of detected metabolic pathways on the class separation observed by OPLS-DA.

SIGNIFICANCE

Through simulated data, we show how these approaches enhance the interpretation of biological effects driving multivariate models and support the identification of altered pathways not detected by univariate analysis. By providing a deeper understanding of metabolic phenotypes, these methods might improve the biological insights derived from statistical and functional analysis of future or previous studies.

Biological and metabolomics-guided isolation of tetrahydrofurofuran lignan from Croton spp. with antiproliferative activity against human melanoma cell line

The Croton genus (Euphorbiaceae) is recognized as a promising source for identifying bioactive compounds with antiproliferative activity. However, knowledge on the chemical composition and activity of Croton floribundus, Croton echinocarpus, and Croton zehntneri is limited. Thus, this study aimed to investigate the antiproliferative activity of these species on cells derived from tumoral breast, lung, and melanoma cells, and primary fibroblasts derived from human skin. Metabolomic strategies were applied via ultra-performance liquid chromatography coupled with high-resolution mass spectrometry and multivariate statistical analysis to target the main active compound. The C. floribundus leaf extract exhibited the highest activity, with an IC50 value lower than that of the reference drug - temozolomide - in the most responsive cell line - SK-MEL-147 - and in all the evaluated melanoma cell lines (SK-MEL-147, CHL-1 and WM-1366). Four tetrahydrofurofuran lignans were isolated for the first time from the most promising fraction of the C. floribundus extract. According to the metabolomic and multivariate statistical analyses, the isolated lignan epi-yangambin constituted the main antiproliferative compound against SK-MEL-147; furthermore, it exhibited selective antiproliferative activity for this cell line (IC50 = 13.09 μg/mL and selectivity index = 3.82; temozolomide, IC50 = 121.50 μg/mL) due to, at least in part, its ability to inhibit cell cycle progression at G2/M. This is especially relevant considering the high resistance of melanoma cells to available drugs. Thus, epi-yangambin can serve as a prototype for further antiproliferative investigations.

The Metabolic and Antioxidant Activity Profiles of Aged Greek Grape Marc Spirits

In the last decade, "expressions" of grape marc spirits aged in wooden barrels of characteristic amber color and complex sensory attributes have been introduced. Yet studies on constituents migrating from the barrel to the beverage are scarce, and their metabolic profile remains unexplored. Furthermore, the literature on the assessment of their antioxidant activity is limited. NMR metabolomics and spectrophotometry have been implemented in 38 samples to elucidate the impact of the aging procedure on the metabolites' composition and establish whether these beverages exhibit antioxidant activity. Provenance was related to fusel alcohols, esters, acetaldehyde, methanol, saccharides, and 2-phenylethanol, while ethyl acetate and ethyl lactate contributed to discriminating samples of the same winery. Identified metabolites such as vanillin, syringaldehyde, and sinapaldehyde were related to the aging procedure. The maturation in the barrel was also associated with an increase in xylose, glucose, fructose, and arabinose. The antioxidant potential of the aged Greek grape marc spirits resulting from their maturation in oak barrels was highlighted. The metabolic profiling and antioxidant potential of aged Greek grape marc spirits were assessed for the first time. Finally, the enrichment of the aromatic region was noted with the presence of metabolites with a furanic and phenolic ring derived, respectively, from the polysaccharides' degradation or the thermal decomposition of lignin.

Advancements in metabolomics research in benign gallbladder diseases: A review

The burgeoning field of metabolomics has piqued the interest of researchers in the context of benign gallbladder diseases, which include conditions such as gallbladder polyps, gallstones, and cholecystitis, which are common digestive system disorders. As metabolomics continues to advance, researchers have increasingly focused their attention on its applicability in the study of benign gallbladder diseases to provide new perspectives for diagnostic, therapeutic, and prognostic evaluation. This comprehensive review primarily describes the techniques of liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance and their respective applications in the study of benign gallbladder disease. Metabolomics has made remarkable progress in various aspects of these diseases, ranging from early diagnosis, etiological research, assessment of disease progression and prognosis, and optimization of therapeutic strategies. However, challenges remain in the field of metabolomics in the study of benign gallbladder diseases. These include issues related to data processing and analysis, biomarker discovery and validation, interdisciplinary research integration, and the advancement of personalized medicine. This article attempts to summarize research findings to date, highlight future research directions, and provide a reference point for metabolomics research in benign gallbladder disease.

Metabolomic profiling of Medicago sativa-derived fungal endophytes and evaluation of their biological activities

This study aimed to discover the potential of Medicago sativa-derived fungal endophytes as a prospective source of bioactive metabolites. In the present study, three different strains of fungal endophyte Aspergillus terreus were isolated from leaves L, roots T and stems St of Medicago sativa to explore their biological and chemical diversity. These isolated fungi were exposed to different fermentation conditions by adding various chemical elicitors to their solid fermentation media. According to LC-HRESIMS-based metabolomics and multivariate analysis, each chemical treatment had a different effect on the chemical profiles of the fungi. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) proposed several compounds with anticancer action against MCF-7 (a human breast cancer cell line) and MDA-MB-231 (a human epithelial breast cancer cell line).

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.

A New Murine Undernutrition Model Based on Complementary Feeding of Undernourished Children Causes Damage to the Morphofunctional Intestinal Epithelium Barrier

BACKGROUND

Complementary feeding is critical in establishing undernutrition. However, experimental undernourished diets do not represent the amount of nutrients in the complementary diets of undernourished children.

OBJECTIVES

To develop, validate, and evaluate the impact of a new murine model of undernutrition on the intestinal epithelium, based on the complementary diet of undernourished children from 7 countries with low-socioeconomic power belonging to the Malnutrition-Enteric Diseases (MAL-ED) cohort study.

METHODS

We used the difference in the percentage of energy, macronutrients, fiber and zinc in the complementary diet of children without undernutrition compared with stunting (height-for-age Z-score < -2) for the MAL-ED diet formulation. Subsequently, C57BL/6 mice were fed a control diet (AIN-93M diet) or MAL-ED diet for 28 d. Weight was measured daily; body composition was measured every 7 d; lactulose:mannitol ratio (LM) and morphometry were evaluated on days 7 and 28; the cotransport test and analysis of intestinal transporters and tight junctions were performed on day 7.

RESULTS

The MAL-ED diet presented -8.03% energy, -37.46% protein, -24.20% lipid, -10.83% zinc, +5.93% carbohydrate, and +45.17% fiber compared with the control diet. This diet rapidly reduced weight gain and compromised body growth and energy reserves during the chronic period (P < 0.05). In the intestinal epithelial barrier, this diet caused an increase in the LM (P < 0.001) and reduced (P < 0.001) the villous area associated with an increase in FAT/CD36 in the acute period and increased (P < 0.001) mannitol excretion in the chronic period.

CONCLUSIONS

The MAL-ED diet induced undernutrition in mice, resulting in acute damage to the integrity of the intestinal epithelial barrier and a subsequent increase in the intestinal area during the chronic period. This study introduces the first murine model of undernutrition for the complementary feeding phase, based on data from undernourished children in 7 different countries.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Metabolites, ions, and the mechanisms behind seasonal cold hardening of Pyrochroa coccinea (Pyrochroidae) larvae

The larvae of the black headed cardinal beetle Pyrochroa coccinea, overwinters under the bark of dead logs in northern European dioecious forests, and are thus exposed to temperatures below the melting point of their bodily fluids. Here we explore the mechanisms behind their seasonal cold hardening by characterising field samples collected monthly throughout the year. Both the lower lethal temperature and supercooling point dropped as much as 10℃ in the second half of November, reaching values around -15℃ by the beginning of December. This change was accompanied by a 320 mosmol/kg increase in hemolymph osmolality, which is a doubling compared to the summer levels. We used NMR metabolomics to identify and measure the absolute concentrations of the responsible cryoprotective C-H containing metabolites in the hemolymph. The largest increase was found to be in either glucose or trehalose, with an average total increase of 120 mM. Proline, alanine, and choline concentrations were found to increase by around 10 mM each. Contrarily, phosphocholine and phosphoethanolamine were halved, resulting in a total decrease of around 50 mM. These measurements were complemented with ion exchange chromatography measurements. This allowed us to account for all the osmotic pressure in the summer hemolymph, and the measured concentration changes explained as much as 40 % of the observed osmolality increase upon cold hardening. Preliminary results indicate that the remainder may be explained by non-colligative protein contributions.

A metabolomics discrimination-based strategy for screening the antithrombin active markers of perilla seeds: A natural oil crop

Natural crops oil with high nutritional value has gradually attracted attention. Perilla seeds are regarded as a source of functional edible oil in America, Asia and European countries due to its abundant nutrients. In this research, samples were extracted by different polarity solvents and evaluated their thrombin inhibition activities in vitro. Metabolomics combined with chemometrics revealed the antithrombin active markers of perilla seeds. The enzyme kinetics and molecular docking results were useful in clarifying their inhibition of thrombin. The orthogonal experimental design was applied to optimize the extraction process of six antithrombin active markers from perilla seeds. The results showed that rosmarinic acid, luteolin, luteolin-7-O-glucoside, α-linolenic acid, linoleic acid, and oleic acid were screened out as functional and active markers. Besides, perilla seeds as a natural oil crop had the potential of antithrombin. It can also be applied in the food field because of its nutraceutical functions. Metabolomics combined with chemometrics will facilitate the discovery of functional, active markers in perilla seeds, which is conducive to accurate quality control.

Metabolomic analysis of the serum and urine of rats exposed to diazinon, dimethoate, and cypermethrin alone or in combination

BACKGROUND

Multiple pesticides are often used in combination for plant protection and public health. Therefore, it is important to analyze the physiological changes induced by multiple pesticides exposure. The objective of this study was to investigate the combined toxicity of the widely-used organophosphorus and pyrethroid pesticides diazinon, dimethoate, and cypermethrin.

METHODS

Male Wistar rats were administrated by gavage once daily with the three pesticides individual or in combination for consecutive 28 days. The metabolic components of serum and urine samples were detected by using 1H nuclear magnetic resonance (NMR)-based metabolomics method. Histopathological examination of liver and kidneys and serum biochemical determination were also carried out.

RESULTS

The results showed that after the 28-day subacute exposure, serum glutamic transaminase and albumin were significantly increased and blood urea nitrogen was significantly decreased in the rats exposed to the mixture of the pesticides compared with the control rats, suggesting that the co-exposure impaired liver and kidney function. Metabolomics analysis indicated that the indicators 14 metabolites were statistically significant altered in the rats after the exposure of the pesticides. The increase in 3-hydroxybutyric acid in urine or decrease of lactate and N-acetyl-L-cysteine in serum could be a potentially sensitive biomarker of the subchronic combined effects of the three insecticides. The reduction level of 2-oxoglutarate and creatinine in urine may be indicative of dysfunction of liver and kidneys.

CONCLUSION

In summary, the exposure of rats to pesticides diazinon, dimethoate, and cypermethrin could cause disorder of lipid and amino acid metabolism, induction of oxidative stress, and dysfunction of liver and kidneys, which contributes to the understanding of combined toxic effects of the pesticides revealed by using the metabolomics analysis of the urine and serum profiles.

Impact of Conventional and Potential New Metal-Based Drugs on Lipid Metabolism in Osteosarcoma MG-63 Cells

This work investigated the mechanisms of action of conventional drugs, cisplatin and oxaliplatin, and the potentially less deleterious drug Pd2Spermine (Spm) and its Pt(II) analog, against osteosarcoma MG-63 cells, using nuclear-magnetic-resonance metabolomics of the cellular lipidome. The Pt(II) chelates induced different responses, namely regarding polyunsaturated-fatty-acids (increased upon cisplatin), suggesting that cisplatin-treated cells have higher membrane fluidity/permeability, thus facilitating cell entry and justifying higher cytotoxicity. Both conventional drugs significantly increased triglyceride levels, while Pt2Spm maintained control levels; this may reflect enhanced apoptotic behavior for conventional drugs, but not for Pt2Spm. Compared to Pt2Spm, the more cytotoxic Pd2Spm (IC50 comparable to cisplatin) induced a distinct phospholipids profile, possibly reflecting enhanced de novo biosynthesis to modulate membrane fluidity and drug-accessibility to cells, similarly to cisplatin. However, Pd2Spm differed from cisplatin in that cells had equivalent (low) levels of triglycerides as Pt2Spm, suggesting the absence/low extent of apoptosis. Our results suggest that Pd2Spm acts on MG-63 cells mainly through adaptation of cell membrane fluidity, whereas cisplatin seems to couple a similar effect with typical signs of apoptosis. These results were discussed in articulation with reported polar metabolome adaptations, building on the insight of these drugs' mechanisms, and particularly of Pd2Spm as a possible cisplatin substitute.

A pilot study of alternative substrates in the critically Ill subject using a ketogenic feed

Bioenergetic failure caused by impaired utilisation of glucose and fatty acids contributes to organ dysfunction across multiple tissues in critical illness. Ketone bodies may form an alternative substrate source, but the feasibility and safety of inducing a ketogenic state in physiologically unstable patients is not known. Twenty-nine mechanically ventilated adults with multi-organ failure managed on intensive care units were randomised (Ketogenic n = 14, Control n = 15) into a two-centre pilot open-label trial of ketogenic versus standard enteral feeding. The primary endpoints were assessment of feasibility and safety, recruitment and retention rates and achievement of ketosis and glucose control. Ketogenic feeding was feasible, safe, well tolerated and resulted in ketosis in all patients in the intervention group, with a refusal rate of 4.1% and 82.8% retention. Patients who received ketogenic feeding had fewer hypoglycaemic events (0.0% vs. 1.6%), required less exogenous international units of insulin (0 (Interquartile range 0-16) vs.78 (Interquartile range 0-412) but had slightly more daily episodes of diarrhoea (53.5% vs. 42.9%) over the trial period. Ketogenic feeding was feasible and may be an intervention for addressing bioenergetic failure in critically ill patients. Clinical Trials.gov registration: NCT04101071.

Unraveling biomarkers of exposure for tenuazonic acid through urinary metabolomics

Mycotoxins are secondary metabolites produced by fungi such as Aspergillus, Alternaria, and Penicillium, affecting nearly 80% of global food crops. Tenuazonic acid (TeA) is the major mycotoxin produced by Alternaria alternata, a prevalent pathogen affecting plants, fruits, and vegetables. TeA is notably prevalent in European diets, however, TeA biomarkers of exposure and metabolites remain unknown. This research aims to bridge this knowledge-gap by gaining insights about human TeA exposure and metabolization. Nine subjects were divided into two groups. The first group received a single bolus of TeA at the Threshold of Toxicological Concern (TTC) to investigate the presence of TeA urinary biomarkers, while the second group served as a control. Sixty-nine urinary samples were prepared and analyzed using UPLC-Xevo TQ-XS for TeA quantification and UPLC-Orbitrap Exploris for polar metabolome acquisition. TeA was rapidly excreted during the first 13 h and the fraction extracted was 0.39 ± 0.22. The polar metabolome compounds effectively discriminating the two groups were filtered using Orthogonal Partial Least Squares-Discriminant Analysis and subsequently annotated (n = 122) at confidence level 4. Finally, the urinary metabolome was compared to in silico predicted TeA metabolites. Nine metabolites, including oxidized, N-alkylated, desaturated, glucuronidated, and sulfonated forms of TeA were detected.

A comparative NMR-based metabolomics study of lung parenchyma of severe COVID-19 patients

COVID-19 was the most significant infectious-agent-related cause of death in the 2020-2021 period. On average, over 60% of those admitted to ICU facilities with this disease died across the globe. In severe cases, COVID-19 leads to respiratory and systemic compromise, including pneumonia-like symptoms, acute respiratory distress syndrome, and multiorgan failure. While the upper respiratory tract and lungs are the principal sites of infection and injury, most studies on the metabolic signatures in COVID-19 patients have been carried out on serum and plasma samples. In this report we attempt to characterize the metabolome of lung parenchyma extracts from fatal COVID-19 cases and compare them with that from other respiratory diseases. Our findings indicate that the metabolomic profiles from fatal COVID-19 and non-COVID-19 cases are markedly different, with the former being the result of increased lactate and amino acid metabolism, altered energy pathways, oxidative stress, and inflammatory response. Overall, these findings provide additional insights into the pathophysiology of COVID-19 that could lead to the development of targeted therapies for the treatment of severe cases of the disease, and further highlight the potential of metabolomic approaches in COVID-19 research.

Bioprospecting-based untargeted metabolomics identifies alkaloids as potential anti-inflammatory bioactive markers of Ocotea species (Lauraceae)

BACKGROUND

Species within the Ocotea genus (Lauraceae), have demonstrated an interesting profile of bioactivities. Renowned for their diverse morphology and intricate specialized metabolite composition, Ocotea species have re-emerged as compelling candidates for bioprospecting in drug discovery research. However, it is a genus insufficiently studied, particularly regarding anti-inflammatory activity.

PURPOSE

To investigate the anti-inflammatory activity of Ocotea spp. extracts and determine the major markers in this genus.

METHODS

Extracts of 60 different Ocotea spp. were analysed by an ex vivo anti-inflammatory assay in human whole blood. The experiment estimates the prostaglandin E2 levels, which is one of the main mediators of the inflammatory cascade, responsible for the classical symptoms of fever, pain, and other common effects of the inflammatory process. Untargeted metabolomics analysis through liquid chromatography coupled with high-resolution mass spectrometry was performed, along with statistical analysis, to investigate which Ocotea metabolites are correlated with their anti-inflammatory activity.

RESULTS

The anti-inflammatory screening indicated that 49 out of 60 Ocotea spp. extracts exhibited significant inhibition of PGE2 release compared to the vehicle (p < 0.05). Furthermore, 10 of these extracts showed statistical similarity to the reference drugs. The bioactive markers were accurately identified using multivariate statistics combined with a fold change (> 1.5) and adjusted false discovery rate analysis as unknown compounds and alkaloids, with a majority of aporphine and benzylisoquinolines. These alkaloids were annotated with an increased level of confidence since MSE spectra were compared with comprehensive databases.

CONCLUSION

This study represents the first bioprospecting report revealing the anti-inflammatory potential of several Ocotea spp. The determination of their anti-inflammatory markers could contribute to drug discovery and the chemical knowledge of the Ocotea genus.

Spoilage markers for freshwater fish: A comprehensive workflow for non-targeted analysis of VOCs using DHS-GC-HRMS

Changes of volatile organic compounds (VOCs) patterns during 6 days of storage at +4 °C were investigated in different freshwater fish species, namely carp and trout, using dynamic headspace gas chromatography time-of-flight mass spectrometry (DHS-GC-TOFMS). DHS parameters were systematically optimized to establish optimum extraction and pre-concentration of VOCs. Moreover, different sample preparation methods were tested: mincing with a manual meat grinder, as well as mincing plus homogenization with a handheld homogenizer both without and with water addition. The addition of water during sample preparation led to pronounced changes of the volatile profiles, depending on the molecular structure and lipophilicity of the analytes, resulting in losses of up to 98 % of more lipophilic compounds (logP > 3). The optimized method was applied to trout and carp. Trout samples of different storage days were compared using univariate (Mann-Whitney U test, fold change calculation) and multivariate (OPLS-DA) statistics. 37 potential spoilage markers were selected; for 11 compounds identity could be confirmed via measurement of authentic standards and 10 compounds were identified by library spectrum match. 22 compounds were also found to be statistically significant spoilage markers in carp. Merging results of the different statistical approaches, the list of 37 compounds could be narrowed down to the 14 most suitable for trout spoilage assessment. This study comprises a systematic evaluation of the capabilities of DHS-GC coupled to high-resolution (HR) MS for studying spoilage in different freshwater fish species, including a comprehensive data evaluation workflow.

Computation-aided studies related to the induction of specialized metabolite biosynthesis in microbial co-cultures: An introductory overview

Co-cultivation is an effective method of inducing the production of specialized metabolites (SMs) in microbial strains. By mimicking the ecological interactions that take place in natural environment, this approach enables to trigger the biosynthesis of molecules which are not formed under monoculture conditions. Importantly, microbial co-cultivation may lead to the discovery of novel chemical entities of pharmaceutical interest. The experimental efforts aimed at the induction of SMs are greatly facilitated by computational techniques. The aim of this overview is to highlight the relevance of computational methods for the investigation of SM induction via microbial co-cultivation. The concepts related to the induction of SMs in microbial co-cultures are briefly introduced by addressing four areas associated with the SM induction workflows, namely the detection of SMs formed exclusively under co-culture conditions, the annotation of induced SMs, the identification of SM producer strains, and the optimization of fermentation conditions. The computational infrastructure associated with these areas, including the tools of multivariate data analysis, molecular networking, genome mining and mathematical optimization, is discussed in relation to the experimental results described in recent literature. The perspective on the future developments in the field, mainly in relation to the microbiome-related research, is also provided.

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

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

Lipopolysaccharides from Ralstonia solanacearum induce a broad metabolomic response in Solanum lycopersicum

Ralstonia solanacearum, one of the most destructive crop pathogens worldwide, causes bacterial wilt disease in a wide range of host plants. The major component of the outer membrane of Gram-negative bacteria, lipopolysaccharides (LPS), has been shown to function as elicitors of plant defense leading to the activation of signaling and defense pathways in several plant species. LPS from a R. solanacearum strain virulent on tomato (LPSR. sol.), were purified, chemically characterized, and structurally elucidated. The lipid A moiety consisted of tetra- to hexa-acylated bis-phosphorylated disaccharide backbone, also decorated by aminoarabinose residues in minor species, while the O-polysaccharide chain consisted of either linear tetrasaccharide or branched pentasaccharide repeating units containing α-L-rhamnose, N-acetyl-β-D-glucosamine, and β-L-xylose. These properties might be associated with the evasion of host surveillance, aiding the establishment of the infection. Using untargeted metabolomics, the effect of LPSR. sol. elicitation on the metabolome of Solanum lycopersicum leaves was investigated across three incubation time intervals with the application of UHPLC-MS for metabolic profiling. The results revealed the production of oxylipins, e.g., trihydroxy octadecenoic acid and trihydroxy octadecadienoic acid, as well as several hydroxycinnamic acid amide derivatives, e.g., coumaroyl tyramine and feruloyl tyramine, as phytochemicals that exhibit a positive correlation to LPSR. sol. treatment. Although the chemical properties of these metabolite classes have been studied, the functional roles of these compounds have not been fully elucidated. Overall, the results suggest that the features of the LPSR. sol. chemotype aid in limiting or attenuating the full deployment of small molecular host defenses and contribute to the understanding of the perturbation and reprogramming of host metabolism during biotic immune responses.

Sevoflurane but not propofol enhances ovarian cancer cell biology through regulating cellular metabolic and signaling mechanisms

Perioperative risk factors, including the choice of anesthetics, may influence ovarian cancer recurrence after surgery. Inhalational anesthetic sevoflurane and intravenous agent propofol might affect cancer cell metabolism and signaling, which, in turn, may influence the malignancy of ovarian cancer cells. The different effects between sevoflurane and propofol on ovarian cancer cell biology and underlying mechanisms were studied. Cultured ovarian cancer cells were exposed to 2.5% sevoflurane, 4 μg/mL propofol, or sham condition as the control for 2 h followed by 24-h recovery. Glucose transporter 1 (GLUT1), mitochondrial pyruvate carrier 1 (MPC1), glutamate dehydrogenase 1 (GLUD1), pigment epithelium-derived factor (PEDF), p-Erk1/2, and hypoxia-inducible factor 1-alpha (HIF-1α) expressions were determined with immunostaining and/or Western blot. Cultured media were collected for 1H-NMR spectroscopy-based metabolomics analysis. Principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were used to analyze metabolomics data. Sevoflurane increased the GLUT1, MPC1, GLUD1, p-Erk1/2, and HIF-1α expressions but decreased the PEDF expression relative to the controls. In contrast to sevoflurane, propofol decreased GLUT1, MPC1, GLUD1, p-Erk1/2, and HIF-1α but increased PEDF expression. Sevoflurane increased metabolite isopropanol and decreased glucose and glutamine energy substrates in the media, but the opposite changes were found after propofol treatment. Our data indicated that, unlike the pro-tumor property of sevoflurane, propofol negatively modulated PEDF/Erk/HIF-1α cellular signaling pathway and inhibited ovarian cancer metabolic efficiency and survival, and hence decreased malignancy. The translational value of this work warrants further study. • Sevoflurane promoted but propofol inhibited ovarian cancer cell biology. • Sevoflurane upregulated but propofol downregulated the GLUT1, MPC1, and GLUD1 expressions of ovarian cancer cells. • Sevoflurane enhanced but propofol inhibited ovarian cancer cellular glucose. metabolism and glutaminolysis. • Sevoflurane downregulated PEDF but upregulated the Erk pathway and HIF-1α, while propofol had the adverse effects on ovarian cancer cells.

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.

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects' hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

Aberrant gut microbiota and fecal metabolites in patients with coal-burning endemic fluorosis in Guizhou, China

Chronic exposure to excessive environmental fluoride has caused fluorosis to become a major public health problem worldwide. Although studies on stress pathways, signaling pathways, and apoptosis induced by fluoride have provided an in-depth understanding of the mechanism of this disease, its exact pathogenesis remains unclear. We hypothesized that the human gut microbiota and metabolome are associated with the pathogenesis of this disease. To get further insight into the profiles of intestinal microbiota and metabolome in coal-burning-induced endemic fluorosis patients, we conducted 16S rRNA sequencing of the intestinal microbial DNA and carried out non-targeted metabolomics of fecal samples from 32 patients with skeletal fluorosis and 33 matched healthy controls in Guizhou, China. We found that the gut microbiota of coal-burning endemic fluorosis patients displayed significant differences in composition, diversity, and abundance compared with healthy controls. This was characterized by an increase in the relative abundance of Verrucomicrobiota, Desulfobacterota, Nitrospirota, Crenarchaeota, Chloroflexi, Myxococcota, Acidobacteriota, Proteobacteria, and unidentified_Bacteria, and a significant decrease in the relative abundance of Firmicutes and Bacteroidetes at the phylum level. Additionally, at the genus level, the relative abundance of some beneficial bacteria, such as Bacteroides, Megamonas, Bifidobacterium, and Faecalibacterium, was significantly reduced. We also demonstrated that, at the genus level, some gut microbial markers, including Anaeromyxobacter, MND1, oc32, Haliangium, and Adurb.Bin063_1, showed potential for identifying coal-burning endemic fluorosis. Moreover, non-targeted metabolomics and correlation analysis revealed the changes in the metabolome, particularly the gut microbiota-derived tryptophan metabolites such as tryptamine, 5-hydroxyindoleacetic acid, and indoleacetaldehyde. Our results indicated that excessive fluoride might cause xenobiotic-mediated dysbiosis of human gut microbiota and metabolic disorders. These findings suggest that the alterations in gut microbiota and metabolome play vital roles in regulating disease susceptibility and multi-organ damage after excessive fluoride exposure.

NMR-Based Metabolomics to Analyze the Effects of a Series of Monoamine Oxidases-B Inhibitors on U251 Cells

Alzheimer’s disease (AD) is a typical progressive neurodegenerative disorder, and with multiple possible pathogenesis. Among them, coumarin derivatives could be used as potential drugs as monoamine oxidase-B (MAO-B) inhibitors. Our lab has designed and synthesized coumarin derivatives based on MAO-B. In this study, we used nuclear magnetic resonance (NMR)-based metabolomics to accelerate the pharmacodynamic evaluation of candidate drugs for coumarin derivative research and development. We detailed alterations in the metabolic profiles of nerve cells with various coumarin derivatives. In total, we identified 58 metabolites and calculated their relative concentrations in U251 cells. In the meantime, the outcomes of multivariate statistical analysis showed that when twelve coumarin compounds were treated with U251cells, the metabolic phenotypes were distinct. In the treatment of different coumarin derivatives, there several metabolic pathways changed, including aminoacyl-tRNA biosynthesis, D-glutamine and D-glutamate metabolism, glycine, serine and threonine metabolism, taurine and hypotaurine metabolism, arginine biosynthesis, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, glutathione metabolism and valine, leucine and isoleucine biosynthesis. Our work documented how our coumarin derivatives affected the metabolic phenotype of nerve cells in vitro. We believe that these NMR-based metabolomics might accelerate the process of drug research in vitro and in vivo.

Beyond cannabinoids: Application of NMR-based metabolomics for the assessment of Cannabis sativa L. crop health

While Cannabis sativa L. varieties have been traditionally characterized by their major cannabinoid profile, it is now well established that other plant metabolites can also have physiological effects, including minor cannabinoids, terpenes, and flavonoids. Given the multiple applications of cannabis in the medical field, it is therefore critical to characterize it according to its chemical composition (i.e., its metabolome) and not only its botanical traits. With this in mind, the cannabinoid and metabolomic profiles from inflorescences of two C. sativa varieties with either high Δ9-tetrahydrocannabinolic acid (THCA) or high cannabidiolic acid (CBDA) contents harvested at different times were studied. According to results from HPLC and NMR-based untargeted metabolomic analyses of organic and aqueous plant material extracts, we show that in addition to expected variations according to cannabinoid profiles, it is possible to distinguish between harvests of the same variety. In particular, it was possible to correlate variations in the metabolome with presence of powdery mildew, leading to the identification of molecular markers associated with this fungal infection in C. sativa.

Metabolomic Changes in Patients Affected by Multiple Sclerosis and Treated with Fingolimod

Current treatment for Multiple Sclerosis (MS) consists of a multidisciplinary approach including disease-modifying therapies. The response to treatment is heterogeneous, representing a crucial challenge in the classification of patients. Metabolomics is an innovative tool that can identifies biomarkers/predictors of treatment response. We aimed to evaluate plasma metabolic changes in a group of naïve Relapsing-Remitting MS patients starting Fingolimod treatment, to find specific metabolomic features that predict the therapeutic response as well as the possible side effects. The study included 42 Relapsing-Remitting MS blood samples, of which 30 were classified as responders after two years of FINGO treatment, whereas 12 patients were Not-Responders. For fifteen patients, samples were collected at four time points: before starting the therapy; at six months after the initiation; at twelve months after; and at twenty-four months after initiation. The serum was analysed through Nuclear Magnetic Resonance and multivariate and univariate statistical analysis. Considering the single comparison between each time point, it was possible to identify a set of metabolites changing their concentrations based on the drug intake. FINGO influences aminoacidic and energy metabolisms and reduces oxidative stress and the activity of the immune system, both typical features of MS.

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

Phenolic Profile, Antioxidant Activity, and Chemometric Classification of Carob Pulp and Products

In recent years, carob and its derived products have gained wide attention due to their health-promoting effects, which are mainly attributed to their phenolic compounds. Carob samples (carob pulps, powders, and syrups) were analyzed to investigate their phenolic profile using high-performance liquid chromatography (HPLC), with gallic acid and rutin being the most abundant compounds. Moreover, the antioxidant capacity and total phenolic content of the samples were estimated through DPPH (IC₅₀ 98.83-488.47 mg extract/mL), FRAP (48.58-144.32 μmol TE/g product), and Folin-Ciocalteu (7.20-23.18 mg GAE/g product) spectrophotometric assays. The effect of thermal treatment and geographical origin of carobs and carob-derived products on their phenolic composition was assessed. Both factors significantly affect the concentrations of secondary metabolites and, therefore, samples' antioxidant activity (p-value < 10^-7). The obtained results (antioxidant activity and phenolic profile) were evaluated via chemometrics, through a preliminary principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). The OPLS-DA model performed satisfactorily, differentiating all samples according to their matrix. Our results indicate that polyphenols and antioxidant capacity can be chemical markers for the classification of carob and its derived products.

Relationships between Molecular Characteristics of Novel Organic Selenium Compounds and the Formation of Sulfur Compounds in Selenium Biofortified Kale Sprouts

Due to problems with selenium deficiency in humans, the search for new organic molecules containing this element in plant biofortification process is highly required. Selenium organic esters evaluated in this study (E-NS-4, E-NS-17, E-NS-71, EDA-11, and EDA-117) are based mostly on benzoselenoate scaffolds, with some additional halogen atoms and various functional groups in the aliphatic side chain of different length, while one compound contains a phenylpiperazine moiety (WA-4b). In our previous study, the biofortification of kale sprouts with organoselenium compounds (at the concentrations of 15 mg/L in the culture fluid) strongly enhanced the synthesis of glucosinolates and isothiocyanates. Thus, the study aimed to discover the relationships between molecular characteristics of the organoselenium compounds used and the amount of sulfur phytochemicals in kale sprouts. The statistical partial least square model with eigenvalues equaled 3.98 and 1.03 for the first and second latent components, respectively, which explained 83.5% of variance in the predictive parameters, and 78.6% of response parameter variance was applied to reveal the existence of the correlation structure between molecular descriptors of selenium compounds as predictive parameters and biochemical features of studied sprouts as response parameters (correlation coefficients for parameters in PLS model in the range-0.521 ÷ 1.000). This study supported the conclusion that future biofortifiers composed of organic compounds should simultaneously contain nitryl groups, which may facilitate the production of plant-based sulfur compounds, as well as organoselenium moieties, which may influence the production of low molecular weight selenium metabolites. In the case of the new chemical compounds, environmental aspects should also be evaluated.

NMR-based metabolomics of plasma from dairy calves infected with two primary causal agents of bovine respiratory disease (BRD)

Each year, bovine respiratory disease (BRD) results in significant economic loss in the cattle sector, and novel metabolic profiling for early diagnosis represents a promising tool for developing effective measures for disease management. Here, ¹H-nuclear magnetic resonance (¹H-NMR) spectra were used to characterize metabolites from blood plasma collected from male dairy calves (n = 10) intentionally infected with two of the main BRD causal agents, bovine respiratory syncytial virus (BRSV) and Mannheimia haemolytica (MH), to generate a well-defined metabolomic profile under controlled conditions. In response to infection, 46 metabolites (BRSV = 32, MH = 33) changed in concentration compared to the uninfected state. Fuel substrates and products exhibited a particularly strong effect, reflecting imbalances that occur during the immune response. Furthermore, ¹H-NMR spectra from samples from the uninfected and infected stages were discriminated with an accuracy, sensitivity, and specificity ≥ 95% using chemometrics to model the changes associated with disease, suggesting that metabolic profiles can be used for further development, understanding, and validation of novel diagnostic tools.

Metabolic Profiling Reveals Changes in Serum Predictive of Venous Ulcer Healing

OBJECTIVE

The aim of this study was to identify potential biomarkers predictive of healing or failure to heal in a population with venous leg ulceration.

SUMMARY BACKGROUND DATA

Venous leg ulceration presents important physical, psychological, social and financial burdens. Compression therapy is the main treatment, but it can be painful and time-consuming, with significant recurrence rates. The identification of a reliable biochemical signature with the ability to identify nonhealing ulcers has important translational applications for disease prognostication, personalized health care and the development of novel therapies.

METHODS

Twenty-eight patients were assessed at baseline and at 20 weeks. Untargeted metabolic profiling was performed on urine, serum, and ulcer fluid, using mass spectrometry and nuclear magnetic resonance spectroscopy.

RESULTS

A differential metabolic phenotype was identified in healing (n = 15) compared to nonhealing (n = 13) venous leg ulcer patients. Analysis of the assigned metabolites found ceramide and carnitine metabolism to be relevant pathways. In this pilot study, only serum biofluids could differentiate between healing and nonhealing patients. The ratio of carnitine to ceramide was able to differentiate between healing phenotypes with 100% sensitivity, 79% specificity, and 91% accuracy.

CONCLUSIONS

This study reports a metabolic signature predictive of healing in venous leg ulceration and presents potential translational applications for disease prognostication and development of targeted therapies.

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study

BACKGROUND

Endometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography-mass spectrometer (GC-MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers.

METHODS

Twenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC-MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis.

RESULTS

Partial least squares discriminant analysis was performed to determine the differences between the two groups (p = 0.003). Threonic acid, 3-hydroxybutyric acid, and proline increased significantly in endometriosis patients, while alanine and valine decreased. ROC curves were built to test the diagnostic power of metabolites. The pathway analysis identified the synthesis and degradation of ketone bodies and the biosynthesis of phenylalanine, tyrosine, and tryptophan as the most altered pathways.

CONCLUSIONS

The metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

Examination of human osteoarchaeological remains as a feasible source of polar and apolar metabolites to study past conditions

Metabolomics is a modern tool that aids in our understanding of the molecular changes in organisms. Archaeological science is a branch of archaeology that explores different archaeological materials using modern analytical tools. Human osteoarchaeological material are a frequent finding in archaeological contexts and have the potential to offer information about previous human populations, which can be illuminating about our current condition. Using a set of samples comprising different skeletal elements and bone structures, here we explore for the first time the possibility of extracting metabolites from osteoarchaeological material. Here, a protocol for extraction and measurement of extracted polar and less-polar/apolar metabolites by ultra-high performance liquid chromatography hyphenated to high resolution mass spectrometry is presented to measure the molecules separated after a reversed phase and hydrophilic interaction liquid chromatography column. Molecular information was obtained, showing that osteoarchaeological material is a viable source of molecular information for metabolomic studies.

Serum metabolomics analysis in patients with alcohol dependence

Objective

Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.

Methods

Liquid chromatography-mass spectrometry (LC-MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.

Results

The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.

Conclusion

The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.

Chickpea and Lupin Sprouts, Stimulated by Different LED Lights, As Novel Examples of Isoflavones-Rich Functional Food, and Their Impact on Breast and Prostate Cells

Among all legumes sprouts' active compounds, isoflavones seem to be the most important; nevertheless, their high content is not always associated with beneficial effects. These compounds may prevent or stimulate hormone-dependent cancers due to their estrogen-like activity. Different LED light quality can change the synthesis of active compounds and significantly influence the biological activity of the sprouts. This study aimed to evaluate the effects of LED light (red, blue, green, yellow), as well as total darkness, and natural light conditions (as reference), on isoflavones content, determined by HPLC-UV-VIS, during 10 days of harvesting of chickpea and lupin sprouts. Due to the ambiguous estrogenic potential of isoflavones, the impact of these sprouts on normal and cancer prostate and breast cells was evaluated. Yellow LED light resulted in the highest sum of isoflavones in chickpea sprouts (up to 1 g/100 g dw), while for green LED light, the isoflavones sum was the lowest. The exact opposite effect was noted for lupin sprouts, with the predominance of green over the yellow LED light. The examined sprouts were of high safety to non-neoplastic breast and prostate cells, with interesting cytotoxic effects on breast MCF7 and prostate DU145 cancer cells. No clear relationship was observed between the activity and isoflavones content.

Comparative Analysis of Acanthopanacis Cortex and Periplocae Cortex Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis

Chinese Herbal Medicines (CHMs) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. The samples of Acanthopanacis Cortex and Periplocae Cortex used were dried cortexes, which are often confused in the market due to their similar appearance, but their chemical composition and odor are different. The clinical use of the two herbs is different, but the phenomenon of being confused with each other often occurs. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two species for fast and robust discrimination, in order to provide a scientific basis for avoiding confusion and misuse in the process of production, circulation and clinical use. In this study, the odor and volatile components of these two medicinal materials were detected by the E-nose and by gas chromatography-mass spectrometry (GC-MS), respectively. An E-nose combined with pattern analysis methods such as principal component analysis (PCA) and partial least squares (PLS) was used to discriminate the cortex samples. The E-nose was used to determine the odors of the samples and enable rapid differentiation of Acanthopanacis Cortex and Periplocae Cortex. GC-MS was utilized to reveal the differences between the volatile constituents of Acanthopanacis Cortex and Periplocae Cortex. In all, 82 components including 9 co-contained components were extracted by chromatographic peak integration and matching, and 24 constituents could be used as chemical markers to distinguish these two species. The E-nose detection technology is able to discriminate between Acanthopanacis Cortex and Periplocae Cortex, with GC-MS providing support to determine the material basis of the E-nose sensors' response. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two medicinal materials by their odors. It can be applied to quality control links such as online detection, and also provide reference for the establishment of other rapid detection methods. The further development and utilization of this technology is conducive to the further supervision of the quality of CHMs and the healthy development of the industry.

Lipidomic analysis of moss species Bryum pseudotriquetrum and Physcomitrium patens under cold stress

Bryophytes, which lack lignin for protection, support themselves in harsh environments by producing various chemicals. In response to cold stress, lipids play a crucial role in cell adaptation and energy storage. Specifically, bryophytes survive at low temperatures by producing very long-chain polyunsaturated fatty acids (vl-PUFAs). The in-depth understanding of the lipid response to cold stress of bryophytes was studied by performing lipid profiling using ultra-high-performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). Two moss species (Bryum pseudotriquetrum and Physcomitrium patens) cultivated at 23°C and at 10°C were included in this study. Relative quantitative lipid concentrations were compared and the potential lipid biomarkers were identified by multivariate statistical analysis in each species. In B. pseudotriquetrum, it was observed that the phospholipids and glycolipids increased under cold stress, while storage lipids decreased. The accumulation of the lipids with high unsaturation degrees mostly appears in phospholipids and glycolipids for both mosses. The results also indicate that two unusual lipid classes in plants, sulfonolipids and phosphatidylmethanol are biosynthesized by the bryophytes. This has not been seen previously and show that bryophytes have a very diverse chemistry and substantially different from other plant groups.

Metabolic profiling on the analysis of different parts of Schisandra chinensis based on UPLC-QTOF-MS with comparative bioactivity assays

The Schisandra chinensis is an important edible plant, and previous phytochemical research focused on the S. chinensis fruit (SF) due to its long history as traditional Chinese medicine. Schisandra chinensis fruit was used as an astringent tonic to astringe the lungs and the kidneys, replenish energy, promote the production of body fluids, tonify the kidney, and induce sedation. The components of S. chinensis, such as its stems (SS), leaves (SL), and roots (SR), have drawn little attention regarding their metabolites and bioactivities. In this study, a strategy of combining a chemical database with the Progenesis QI informatics platform was applied to characterize the metabolites. A total of 332 compounds were tentatively identified, including lignans, triterpenoids, flavonoids, tannins, and other compound classes. Heatmap and principal component analysis (PCA) showed remarkable differences in different parts of the plants. By multiple orthogonal partial least-squares discriminant analyses (OPLS-DA), 76 compounds were identified as potential marker compounds that differentiate these different plant parts. Based on the variable influence on the projection score from OPLS-DA, the active substances including gomisin D, schisandrol B, schisantherin C, kadsuranin, and kadlongilactone F supported the fact that the biological activity of the roots was higher than that of the fruit. These substances can be used as marker compounds in the plant roots, which likely contribute to their antioxidant and anti-inflammatory activities. The plant roots could be a new medicinal source that exhibits better activity than that of traditional medicinal parts, which makes them worth exploring.

An Intracellular Metabolic Signature as a Potential Donor-Independent Marker of the Osteogenic Differentiation of Adipose Tissue Mesenchymal Stem Cells

This paper describes an untargeted NMR metabolomics study to identify potential intracellular donor-dependent and donor-independent metabolic markers of proliferation and osteogenic differentiation of human adipose mesenchymal stem cells (hAMSCs). The hAMSCs of two donors with distinct proliferating/osteogenic characteristics were fully characterized regarding their polar endometabolome during proliferation and osteogenesis. An 18-metabolites signature (including changes in alanine, aspartate, proline, tyrosine, ATP, and ADP, among others) was suggested to be potentially descriptive of cell proliferation, independently of the donor. In addition, a set of 11 metabolites was proposed to compose a possible donor-independent signature of osteogenesis, mostly involving changes in taurine, glutathione, methylguanidine, adenosine, inosine, uridine, and creatine/phosphocreatine, choline/phosphocholine and ethanolamine/phosphocholine ratios. The proposed signatures were validated for a third donor, although they require further validation in a larger donor cohort. We believe that this proof of concept paves the way to exploit metabolic markers to monitor (and potentially predict) cell proliferation and the osteogenic ability of different donors.

Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives

Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.

Multi-omics research strategies in ischemic stroke: A multidimensional perspective

Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.

Application of Metabolomics in Fungal Research

Metabolomics is an essential method to study the dynamic changes of metabolic networks and products using modern analytical techniques, as well as reveal the life phenomena and their inherent laws. Currently, more and more attention has been paid to the development of metabolic histochemistry in the fungus field. This paper reviews the application of metabolomics in fungal research from five aspects: identification, response to stress, metabolite discovery, metabolism engineering, and fungal interactions with plants.