Project description:Color is a major quality trait of rosé wines due to their packaging in clear glass bottles. This color is due to the presence of phenolic pigments extracted from grapes to wines and products of reactions taking place during the wine-making process. This study focuses on changes occurring during the alcoholic fermentation of Syrah, Grenache and Cinsault musts, which were conducted at laboratory (250 mL) and pilot (100 L) scales. The color and phenolic composition of the musts and wines were analyzed using UV-visible spectrophotometry, and metabolomics fingerprints were acquired by ultra-high performance liquid chromatography-high-resolution mass spectrometry. Untargeted metabolomics data highlighted markers of fermentation stage (must or wine) and markers related to the grape variety (e.g., anthocyanins in Syrah, hydroxycinnamates and tryptophan derivatives in Grenache, norisoprenoids released during fermentation in Cinsault). Cinsault wines contained higher molecular weight compounds possibly resulting from the oxidation of phenolics, which may contribute to their high absorbance values.
Project description:Untargeted metabolomics is a powerful tool in chemical fingerprinting. It can be applied in phytochemistry to aid species identification, systematic studies and quality control of bioproducts. This approach aims to produce as much chemical information as possible, without focusing on any specific chemical class, thus, requiring extensive chemometric effort. This study aimed to evaluate the feasibly of an untargeted metabolomics method in phytochemistry by a study case of the Copaifera genus (Fabaceae). This genus contains significant medicinal species used worldwidely. Copaifera exploitation issues include a lack of chemical data, ambiguous species identification methods and absence of quality control for its bioproducts. Different organs of five Copaifera species were analysed by UHPLC-HRMS/MS, GNPS platform and chemometric tools. Untargeted metabolomics enabled the identification of 19 chemical markers and 29 metabolites, distinguishing each sample by species, plant organs, and biome type. Chemical markers were classified as flavonoids, terpenoids and condensed tannins. The applied method provided reliable information about species chemodiversity using fast workflow with little sampling size. The untargeted approach by UHPLC-HRMS/MS proved to be a promising tool for species identification, pharmacological prospecting and in the future for the quality control of extracts used in the manufacture of bioproducts.
Project description:Chemical composition of propolis depends on the plant source and thus on the geographic and climatic characteristics of the site of collection. The aim of this study was to investigate the chemical profile of Greek and Chinese propolis extracts from different regions and suggest similarities and differences between them. Untargeted ultrahigh-performance liquid chromatography coupled to hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-HRMS) method was developed and 22 and 23 propolis samples from Greece and China, respectively, were analyzed. The experimental data led to the observation that there is considerable variability in terms of quality of the distinctive propolis samples. Partial least squares - discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models were constructed and allowed the identification of significant features for sample discrimination, adding relevant information for the identification of class-determining metabolites. Chinese samples overexpressed compounds that are characteristic of the poplar type propolis, whereas Greek samples overexpress the latter and the diterpenes characteristic of the Mediterranean propolis type.
Project description:Soapberry (Sapindus mukorossi Gaertn.) is a multi-functional tree with widespread application in toiletries, biomedicine, biomass energy, and landscaping. The pericarp of soapberry can be used as a medicine or detergent. However, there is currently no systematic study on the chemical constituents of soapberry pericarp during fruit development and ripening, and the dynamic changes in these constituents still unclear. In this study, a non-targeted metabolomics approach using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) was used to comprehensively profile the variations in metabolites in the soapberry pericarp at eight fruit growth stages. The metabolome coverage of UHPLC-HRMS on a HILIC column was higher than that of a C18 column. A total of 111 metabolites were putatively annotated. Principal component analysis and hierarchical clustering analysis of pericarp metabolic composition revealed clear metabolic shifts from early (S1-S2) to late (S3-S5) development stages to fruit ripening stages (S6-S8). Furthermore, pairwise comparison identified 57 differential metabolites that were involved in 18 KEGG pathways. Early fruit development stages (S1-S2) were characterized by high levels of key fatty acids, nucleotides, organic acids, and phosphorylated intermediates, whereas fruit ripening stages (S6-S8) were characterized by high contents of bioactive and valuable metabolites, such as troxipide, vorinostat, furamizole, alpha-tocopherol quinone, luteolin, and sucrose. S8 (fully developed and mature stage) was the most suitable stage for fruit harvesting to utilize the pericarp. To the best of our knowledge, this was the first metabolomics study of the soapberry pericarp during whole fruit growth. The results could offer valuable information for harvesting, processing, and application of soapberry pericarp, as well as highlight the metabolites that could mediate the biological activity or properties of this medicinal plant.
Project description:Dysregulation of cellular metabolism is now a well-recognized hallmark of cancer. Studies investigating the metabolic features of cancer cells have shed new light onto processes in cancer cell biology and have identified many potential novel treatment options. The advancement of mass spectrometry-based metabolomics has improved the ability to monitor multiple metabolic pathways simultaneously in various experimental settings. However, questions still remain as to how certain steps in the metabolite extraction process affect the metabolic profiles of cancer cells. Here, we use ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) untargeted metabolomics to investigate the effects of different detachment and lysis methods on the types and abundances of metabolites extracted from MDA-MB-231 cells through the use of in-house standards libraries and pathway analysis software. Results indicate that detachment methods (trypsinization vs. scraping) had the greatest effect on metabolic profiles whereas lysis methods (homogenizer beads vs. freeze-thaw cycling) had a lesser, though still significant, effect. No singular method was clearly superior over others, with certain metabolite classes giving higher abundances or lower variation for each detachment-lysis combination. These results indicate the importance of carefully selecting sample preparation methods for cell-based metabolomics to optimize the extraction performance for certain compound classes.
Project description:IntroductionOsteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. An increasing number of studies have demonstrated that tumor proliferation and metastasis are closely related to complex metabolic reprogramming. However, there are limited data to provide a comprehensive metabolic picture of osteosarcoma.ObjectivesOur study aims to identify aberrant metabolic pathways and seek potential adjuvant biomarkers for osteosarcoma.MethodsSerum samples were collected from 65 osteosarcoma patients and 30 healthy controls. Nontargeted metabolomic profiling was performed by liquid chromatography-mass spectrometry (LC-MS) based on univariate and multivariate statistical analyses.ResultsThe OPLS-DA model analysis identified clear separations among groups. We identified a set of differential metabolites such as higher serum levels of adenosine-5-monophosphate, inosine-5-monophosphate and guanosine monophosphate in primary OS patients compared to healthy controls, and higher serum levels of 5-aminopentanamide, 13(S)-HpOTrE (FA 18:3 + 2O) and methionine sulfoxide in lung metastatic OS patients compared to primary OS patients, revealing aberrant metabolic features during the proliferation and metastasis of osteosarcoma. We found a group of metabolites especially lactic acid and glutamic acid, with AUC values of 0.97 and 0.98, which could serve as potential adjuvant diagnostic biomarkers for primary osteosarcoma, and a panel of 2 metabolites, 5-aminopentanamide and 13(S)-HpOTrE (FA 18:3 + 2O), with an AUC value of 0.92, that had good monitoring ability for lung metastases.ConclusionsOur study provides new insight into the aberrant metabolic features of osteosarcoma. The potential biomarkers identified here may have translational significance.
Project description:The development of a colorectal adenoma (CA) into carcinoma (CRC) is a long and stealthy process. There remains a lack of reliable biomarkers to distinguish CA from CRC. To effectively explore underlying molecular mechanisms and identify novel lipid biomarkers promising for early diagnosis of CRC, an ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS) method was employed to comprehensively measure lipid species in human serum samples of patients with CA and CRC. Results showed significant differences in serum lipid profiles between CA and CRC groups, and 85 differential lipid species (P < 0.05 and fold change > 1.50 or < 0.67) were discovered. These significantly altered lipid species were mainly involved in fatty acid (FA), phosphatidylcholine (PC), and triacylglycerol (TAG) metabolism with the constituent ratio > 63.50%. After performance evaluation by the receiver operating characteristic (ROC) curve analysis, seven lipid species were ultimately proposed as potential biomarkers with the area under the curve (AUC) > 0.800. Of particular value, a lipid panel containing docosanamide, SM d36:0, PC 36:1e, and triheptanoin was selected as a composite candidate biomarker with excellent performance (AUC = 0.971), and the highest selected frequency to distinguish patients with CA from patients with CRC based on the support vector machine (SVM) classification model. To our knowledge, this study was the first to undertake a lipidomics profile using serum intended to identify screening lipid biomarkers to discriminate between CA and CRC. The lipid panel could potentially serve as a composite biomarker aiding the early diagnosis of CRC. Metabolic dysregulation of FAs, PCs, and TAGs seems likely involved in malignant transformation of CA, which hopefully will provide new clues to understand its underlying mechanism.
Project description:Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (1H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.
Project description:Glucosinolates (GSLs) and their degradation products in radish confer plant defense, promote human health, and generate pungent flavor. However, the intact GSLs in radish have not been investigated comprehensively yet. Here, an accurate qualitative and quantitative analyses of 15 intact GSLs from radish, including four major GSLs of glucoraphasatin (GRH), glucoerucin (GER), glucoraphenin (GRE), and 4-methoxyglucobrassicin (4MGBS), were conducted using UHPLC-HRMS/MS in combination with UHPLC-QqQ-MS/MS. Simultaneously, three isomers of hexyl GSL, 3-methylpentyl GSL, and 4-methylpentyl GSL were identified in radish. The highest content of GSLs was up to 232.46 μmol/g DW at the 42 DAG stage in the 'SQY' taproot, with an approximately 184.49-fold increase compared to the lowest content in another sample. That the GSLs content in the taproots of two radishes fluctuated in a similar pattern throughout the five vegetative growth stages according to the metabolic profiling, whereas the GSLs content in the '55' leaf steadily decreased over the same period. Additionally, the proposed biosynthetic pathways of radish-specific GSLs were elucidated in this study. Our findings will provide an abundance of qualitative and quantitative data on intact GSLs, as well as a method for detecting GSLs, thus providing direction for the scientific progress and practical utilization of GSLs in radish.
Project description:(1) Background: Citrus honey constitutes a unique monofloral honey characterized by a distinctive aroma and unique taste. The non-targeted chemical analysis can provide pivotal information on chemical markers that differentiate honey based on its geographical and botanical origin. (2) Methods: Within the PRIMA project "PLANT-B", a metabolomics workflow was established to unveil potential chemical markers of orange blossom honey produced in case study areas of Egypt, Italy, and Greece. In some of these areas, aromatic medicinal plants were cultivated to enhance biodiversity and attract pollinators. The non-targeted chemical analysis and metabolomics were conducted using ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). (3) Results: Forty compounds were disclosed as potential chemical markers, enabling the differentiation of the three orange blossom honeys according to geographical origin. Italian honey showed a preponderance of flavonoids, while in Greek honey, terpenoids and iridoids were more abundant than flavonoids, except for hesperidin. In Egyptian honey, suberic acid and a fatty acid ester derivative emerged as chemical markers. New, for honey, furan derivatives were identified using GC-MS in Greek samples. (4) Conclusions: The application of UHPLC-HRMS metabolomics combined with an elaborate melissopalynological analysis managed to unveil several potential markers of Mediterranean citrus honey potentially associated with citrus crop varieties and the local indigenous flora.