Browse
Submit Data
Databases
API
Help

Dataset Information

29 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Differentiation of industrial hemp strains by their cannabinoid and phenolic compounds using LC × LC-HRMS.

ABSTRACT: Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ⁹-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains.

SUBMITTER: Montero L

PROVIDER: S-EPMC9242925 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Analysis of Phenolic Compounds in Commercial Cannabis sativa L. Inflorescences Using UHPLC-Q-Orbitrap HRMS.

Project description:Industrial hemp (Cannabis sativa L. Family Cannabaceae) contains a vast number of bioactive relevant compounds, namely polyphenols including flavonoids, phenolic acids, phenol amides, and lignanamides, well known for their therapeutic properties. Nowadays, many polyphenols-containing products made of herbal extracts are marketed, claiming to exert health-promoting effects. In this context, industrial hemp inflorescence may represent an innovative source of bioactive compounds to be used in nutraceutical formulations. The aim of this work was to provide a comprehensive analysis of the polyphenolic fraction contained in polar extracts of four different commercial cultivars (Kompoti, Tiborszallasi, Antal, and Carmagnola Cs) of hemp inflorescences through spectrophotometric (TPC, DPPH tests) and spectrometry measurement (UHPLC-Q-Orbitrap HRMS). Results highlighted a high content of cannflavin A and B in inflorescence analyzed samples, which appear to be cannabis-specific, with a mean value of 61.8 and 84.5 mg/kg, meaning a ten-to-hundred times increase compared to other parts of the plant. Among flavonols, quercetin-3-glucoside reached up to 285.9 mg/kg in the Carmagnola CS cultivar. Catechin and epicatechin were the most representative flavanols, with a mean concentration of 53.3 and 66.2 mg/kg, respectively, for all cultivars. Total polyphenolic content in inflorescence samples was quantified in the range of 10.51 to 52.58 mg GAE/g and free radical-scavenging included in the range from 27.5 to 77.6 mmol trolox/kg. Therefore, C. sativa inflorescence could be considered as a potential novel source of polyphenols intended for nutraceutical formulations.

| S-EPMC7037164 | biostudies-literature

Machine Learning for Absolute Quantification of Unidentified Compounds in Non-Targeted LC/HRMS.

Project description:LC/ESI/HRMS is increasingly employed for monitoring chemical pollutants in water samples, with non-targeted analysis becoming more common. Unfortunately, due to the lack of analytical standards, non-targeted analysis is mostly qualitative. To remedy this, models have been developed to evaluate the response of compounds from their structure, which can then be used for quantification in non-targeted analysis. Still, these models rely on tentatively known structures while for most detected compounds, a list of structural candidates, or sometimes only exact mass and retention time are identified. In this study, a quantification approach was developed, where LC/ESI/HRMS descriptors are used for quantification of compounds even if the structure is unknown. The approach was developed based on 92 compounds analyzed in parallel in both positive and negative ESI mode with mobile phases at pH 2.7, 8.0, and 10.0. The developed approach was compared with two baseline approaches- one assuming equal response factors for all compounds and one using the response factor of the closest eluting standard. The former gave a mean prediction error of a factor of 29, while the latter gave a mean prediction error of a factor of 1300. In the machine learning-based quantification approach developed here, the corresponding prediction error was a factor of 10. Furthermore, the approach was validated by analyzing two blind samples containing 48 compounds spiked into tap water and ultrapure water. The obtained mean prediction error was lower than a factor of 6.0 for both samples. The errors were found to be comparable to approaches using structural information.

| S-EPMC8840743 | biostudies-literature

Dispersive magnetic solid-phase extraction for capsaicinoid compounds in human serum using LC-HRMS: targeted and non-targeted approaches.

Project description:A new analytical method based on the use of dispersive magnetic solid-phase extraction (DMSPE) is described for the preconcentration of capsaicin (CAP), dihydrocapsaicin (DCAP), and N-vanillylnonanamide (PCAP) from human serum samples. The influence of several experimental factors affecting the adsorption (nature and amount of magnetic material, adsorption time, and pH) and desorption (nature of solvent, its volume and desorption time) steps was studied. Among seven different nanomaterials studied, the best results were obtained using magnetic multiwalled carbon nanotubes, which were characterized by means of spectrometry- and microscopy-based techniques. Analyses were performed by ultra-high-performance liquid chromatography with quadrupole-time-of-flight mass spectrometry using electrospray ionization in positive mode (UHPLC-ESI-Q-TOF-MS). The developed method was validated by obtaining several parameters, including linearity (0.3-300 μg L-1 range), and limits of detection which were 0.1, 0.15, and 0.17 μg L-1 for CAP, DCAP, and PCAP, respectively. The repeatability of the method, expressed as relative standard deviation (RSD, n = 7), varied from 3.4 to 11%. The serum samples were also studied through a non-targeted approach in a search for capsaicinoid metabolites and related compounds. With this objective, the fragmentation pathway of this family of compounds was initially studied and a strategy was established for the identification of novel or less studied capsaicinoid-derived compounds.

| S-EPMC10079705 | biostudies-literature

Non-targeted analysis of unexpected food contaminants using LC-HRMS.

Project description:A non-target analysis method for unexpected contaminants in food is described. Many current methods referred to as "non-target" are capable of detecting hundreds or even thousands of contaminants. However, they will typically still miss all other possible contaminants. Instead, a metabolomics approach might be used to obtain "true non-target" analysis. In the present work, such a method was optimized for improved detection capability at low concentrations. The method was evaluated using 19 chemically diverse model compounds spiked into milk samples to mimic unknown contamination. Other milk samples were used as reference samples. All samples were analyzed with UHPLC-TOF-MS (ultra-high-performance liquid chromatography time-of-flight mass spectrometry), using reversed-phase chromatography and electrospray ionization in positive mode. Data evaluation was performed by the software TracMass 2. No target lists of specific compounds were used to search for the contaminants. Instead, the software was used to sort out all features only occurring in the spiked sample data, i.e., the workflow resembled a metabolomics approach. Procedures for chemical identification of peaks were outside the scope of the study. Method, study design, and settings in the software were optimized to minimize manual evaluation and faulty or irrelevant hits and to maximize hit rate of the spiked compounds. A practical detection limit was established at 25 ?g/kg. At this concentration, most compounds (17 out of 19) were detected as intact precursor ions, as fragments or as adducts. Only 2 irrelevant hits, probably natural compounds, were obtained. Limitations and possible practical use of the approach are discussed.

| S-EPMC6096699 | biostudies-literature

Identification of In Vitro Metabolites of Synthetic Phenolic Antioxidants BHT, BHA, and TBHQ by LC-HRMS/MS.

Project description:Butylated hydroxytoluene (BHT) and its analogs, butylated hydroxyanisole (BHA) and tert-butyl-hydroquinone (TBHQ), are widely used synthetic preservatives to inhibit lipid oxidation in the food, cosmetic and pharmaceutical industries. Despite their widespread use, little is known about their human exposure and related biotransformation products. The metabolism of these compounds was investigated using in vitro incubations with human and rat liver fractions. Liquid chromatography coupled to high-resolution tandem mass spectrometry was employed to detect and characterize stable and reactive species formed via oxidative metabolism, as well as phase II conjugates. Several oxidative metabolites have been detected, as well as glutathione, glucuronide, and sulfate conjugates, many of which were not previously reported. A combination of accurate mass measurements, MS/MS fragmentation behavior, and isotope-labeling studies were used to elucidate metabolite structures.

| S-EPMC7765162 | biostudies-literature

Analysis of Phenolic Compositions in Cranberry Dietary Supplements using UHPLC-HRMS.

Project description:The potential human health benefits of American cranberry (Vaccinium macrocarpon Ait.) leads to the popularity of its dietary supplements in the U.S. market. However, the qualities of the cranberry dietary supplements (CDSs) have never been carefully evaluated. In this study, the phenolic components in ten different CDSs were analyzed using ultra-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). The study found quercetin and myricetin aglycones in most CDSs, but not in cranberry fruits, despite otherwise similar phenolic profiles between CDS and cranberry fruits in general. One supplement with high levels of B-type proanthocyanidins and non-cranberry flavonol rutin was determined to be adulterated by other botanical extracts. The CDSs only possessed 4% to 11% of the phenolic contents comparing to their claimed fresh cranberry equivalents, emphasizing the urgency of standardized product quality control and labelling for CDS manufacture and marketing.

| S-EPMC7451253 | biostudies-literature

Guide to Semi-Quantitative Non-Targeted Screening Using LC/ESI/HRMS.

Project description:Non-targeted screening (NTS) with reversed phase liquid chromatography electrospray ionization high resolution mass spectrometry (LC/ESI/HRMS) is increasingly employed as an alternative to targeted analysis; however, it is not possible to quantify all compounds found in a sample with analytical standards. As an alternative, semi-quantification strategies are, or at least should be, used to estimate the concentrations of the unknown compounds before final decision making. All steps in the analytical chain, from sample preparation to ionization conditions and data processing can influence the signals obtained, and thus the estimated concentrations. Therefore, each step needs to be considered carefully. Generally, less is more when it comes to choosing sample preparation as well as chromatographic and ionization conditions in NTS. By combining the positive and negative ionization mode, the performance of NTS can be improved, since different compounds ionize better in one or the other mode. Furthermore, NTS gives opportunities for retrospective analysis. In this tutorial, strategies for semi-quantification are described, sources potentially decreasing the signals are identified and possibilities to improve NTS are discussed. Additionally, examples of retrospective analysis are presented. Finally, we present a checklist for carrying out semi-quantitative NTS.

| S-EPMC8228683 | biostudies-literature

The Analysis of Phenolic Compounds in Walnut Husk and Pellicle by UPLC-Q-Orbitrap HRMS and HPLC.

Project description:Husk and pellicle as the agri-food waste in the walnut-product industry are in soaring demand because of their rich polyphenol content. This study investigated the differential compounds related to walnut polyphenol between husk and pellicle during fruit development stage. By using ultra-high performance liquid chromatography-quadrupole-orbitrap (UHPLC-Q-Orbitrap), a total of 110 bioactive components, including hydrolysable tannins, flavonoids, phenolic acids and quinones, were tentatively identified, 33 of which were different between husk and pellicle. The trend of dynamic content of 16 polyphenols was clarified during walnut development stage by high-performance liquid chromatography (HPLC). This is the first time to comprehensive identification of phenolic compounds in walnut husk and pellicle, and our results indicated that the pellicle is a rich resource of polyphenols. The dynamic trend of some polyphenols was consistent with total phenols. The comprehensive characterization of walnut polyphenol and quantification of main phenolic compounds will be beneficial for understanding the potential application value of walnut and for exploiting its metabolism pathway.

| S-EPMC8158686 | biostudies-literature

Analysis of Selected Phenolic Compounds in Organic, Pesticide-Free, Conventional Rice (Oryza sativa L.) Using LC-ESI-MS/MS.

Project description:Rice (Oryza sativa L.) contains generous amounts of carbohydrates, proteins, vitamins, and dietary fibers, in addition to secondary metabolites such as phenols and flavonoids that act as antioxidants. The phenolic compounds detected in rice (organic rice (OR), conventional rice (CR), and pesticide-free rice (PFR)), namely, protocatechuic, gentisic, p-hydroxybenzoic, p-coumaric, ferulic, salicylic, and caffeic acids, are notable free radical scavengers. The sum of these phenolic compounds was found to be higher in PFR, followed by CR and OR (p < 0.0001), when the rice types were classified based on the farming system employed. In addition, significant differences were observed in the p-hydroxybenzoic acid levels for the OR and CR groups compared with the PFR groups (p < 0.01). Furthermore, greater quantities of p-coumaric acid were found in CR-08 and OR-02, although these groups contained overall higher and lower sums of phenolic compounds, respectively. Moreover, significance was observed in the sum of the phenolic compounds, although only small quantities were found in polished rice. Further research is thus required to provide a clearer picture regarding the phenolic profiles of different rice brands.

| S-EPMC6337394 | biostudies-literature

Selection and validation of reference genes for normalization of qRT-PCR data to study the cannabinoid pathway genes in industrial hemp.

Project description:There has been significant interest in researching the pharmaceutical applications of Industrial hemp since its legalization three years ago. The crop is mostly dioecious and known for its production of phytocannabinoids, flavonoids, and terpenes. Although many scientific reports have showed gene expression analysis of hemp through OMICs approaches, unreliable reference genes for normalization of qRT-PCR data make it difficult to validate the OMICs data. Four software packages: geNorm, NormFinder, BestKeeper, and RefFinder were used to evaluate the differential gene expression patterns of 13 candidate reference genes under osmotic, heavy metal, hormonal, and UV stresses. EF-1α ranked as the most stable reference gene across all stresses, TUB was the most stable under osmotic stress, and TATA was the most stable under both heavy metal stress and hormonal stimuli. The expression patterns of two cannabinoid pathway genes, AAE1 and CBDAS, were used to validate the reliability of the selected reference genes. This work provides useful information for gene expression characterization in hemp and future research in the synthesis, transport, and accumulation of secondary metabolites.

| S-EPMC8687539 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data