scholarly journals Large-Scale Non-Targeted Metabolomics Reveals Antioxidant, Nutraceutical and Therapeutic Potentials of Sorghum

Antioxidants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1511
Author(s):  
Ajay Prasanth Ramalingam ◽  
Williams Mohanavel ◽  
Ameena Premnath ◽  
Raveendran Muthurajan ◽  
P. V. Vara Prasad ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Partial Least Square ◽  
Least Square ◽  
Mass Spectrometry Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Genetic Profile ◽  
Grain Color ◽  
Independent Analysis ◽  
Food And Feed

Sorghum is one of the most important food and feed cereal crops and has been gaining industrial importance in recent years for its biofuel, nutraceutical and antioxidant values. A genetic profile variation study was undertaken for the accumulation of phytochemicals in 61 diverse sorghum accessions differing in their growth habitat and grain color through non-targeted Gas Chromatography–Mass Spectrometry (GC-MS/MS) analysis. Mass Spectrometry–Data Independent AnaLysis (MS-DIAL) and MetaboAnalyst identified 221 metabolites belonging to 27 different phytochemicals. Tropical and temperate sorghums were distinct in their metabolic profiles with minimum overlaps, and 51 different metabolites were crucial in differentiating the two groups. Temperate sorghums had the ability to accumulate more of phenolic acids, phytosterols, flavonoids, carotenoids, and tropical sorghums for stress-related amino acids, sugars and fatty acids. Grain-color-based Partial Least Square–Discriminant Analysis (PLS-DA) analysis identified 94 Variable Importance in Projections (VIP) metabolites containing majority of flavonoids, phenylpropanoids and phytosterols. This study identified two sorghum lines (IS 7748 and IS 14861) with rich amounts of antioxidants (catechins and epicatechins) belonging to the group of condensed tannins that otherwise do not accumulate commonly in sorghum. Out of 13 metabolic pathways identified, flavonoid biosynthesis showed the highest expression. This study provided new opportunities for developing biofortified sorghum with enhanced nutraceutical and therapeutics through molecular breeding and metabolic engineering.

scholarly journals Characterization of α-Glucosidase Inhibitors from Clinacanthus nutans Lindau Leaves by Gas Chromatography-Mass Spectrometry-Based Metabolomics and Molecular Docking Simulation

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2402 ◽  
Author(s):  
Suganya Murugesu ◽  
Zalikha Ibrahim ◽  
Qamar-Uddin Ahmed ◽  
Nik-Idris Nik Yusoff ◽  
Bisha-Fathamah Uzir ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Molecular Docking ◽  
Acid Methyl Ester ◽  
Docking Simulation ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Glucosidase Inhibitors ◽  
Clinacanthus Nutans

Background: Clinacanthus nutans (C. nutans) is an Acanthaceae herbal shrub traditionally consumed to treat various diseases including diabetes in Malaysia. This study was designed to evaluate the α-glucosidase inhibitory activity of C. nutans leaves extracts, and to identify the metabolites responsible for the bioactivity. Methods: Crude extract obtained from the dried leaves using 80% methanolic solution was further partitioned using different polarity solvents. The resultant extracts were investigated for their α-glucosidase inhibitory potential followed by metabolites profiling using the gas chromatography tandem with mass spectrometry (GC-MS). Results: Multivariate data analysis was developed by correlating the bioactivity, and GC-MS data generated a suitable partial least square (PLS) model resulting in 11 bioactive compounds, namely, palmitic acid, phytol, hexadecanoic acid (methyl ester), 1-monopalmitin, stigmast-5-ene, pentadecanoic acid, heptadecanoic acid, 1-linolenoylglycerol, glycerol monostearate, alpha-tocospiro B, and stigmasterol. In-silico study via molecular docking was carried out using the crystal structure Saccharomyces cerevisiae isomaltase (PDB code: 3A4A). Interactions between the inhibitors and the protein were predicted involving residues, namely LYS156, THR310, PRO312, LEU313, GLU411, and ASN415 with hydrogen bond, while PHE314 and ARG315 with hydrophobic bonding. Conclusion: The study provides informative data on the potential α-glucosidase inhibitors identified in C. nutans leaves, indicating the plant’s therapeutic effect to manage hyperglycemia.

scholarly journals Detecting Pulmonary Oxygen Toxicity Using eNose Technology and Associations between Electronic Nose and Gas Chromatography–Mass Spectrometry Data

Metabolites ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 286
Author(s):  
Thijs T. Wingelaar ◽  
Paul Brinkman ◽  
Rianne de Vries ◽  
Pieter-Jan A.M. van Ooij ◽  
Rigo Hoencamp ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Oxygen Toxicity ◽  
Partial Least Square ◽  
Least Square ◽  
Sensor Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Exhaled Breath ◽  
Chromatography Mass Spectrometry

Exposure to oxygen under increased atmospheric pressures can induce pulmonary oxygen toxicity (POT). Exhaled breath analysis using gas chromatography–mass spectrometry (GC–MS) has revealed that volatile organic compounds (VOCs) are associated with inflammation and lipoperoxidation after hyperbaric–hyperoxic exposure. Electronic nose (eNose) technology would be more suited for the detection of POT, since it is less time and resource consuming. However, it is unknown whether eNose technology can detect POT and whether eNose sensor data can be associated with VOCs of interest. In this randomized cross-over trial, the exhaled breath from divers who had made two dives of 1 h to 192.5 kPa (a depth of 9 m) with either 100% oxygen or compressed air was analyzed, at several time points, using GC–MS and eNose. We used a partial least square discriminant analysis, eNose discriminated oxygen and air dives at 30 min post dive with an area under the receiver operating characteristics curve of 79.9% (95%CI: 61.1–98.6; p = 0.003). A two-way orthogonal partial least square regression (O2PLS) model analysis revealed an R² of 0.50 between targeted VOCs obtained by GC–MS and eNose sensor data. The contribution of each sensor to the detection of targeted VOCs was also assessed using O2PLS. When all GC–MS fragments were included in the O2PLS model, this resulted in an R² of 0.08. Thus, eNose could detect POT 30 min post dive, and the correlation between targeted VOCs and eNose data could be assessed using O2PLS.

scholarly journals Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis to Identify the Alpha Glucosidase Inhibitors from Flesh of Salacca zalacca Fruits and Their Molecular Docking Studies

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Mohammed S. M. Saleh ◽  
Mohammad Jamshed Siddiqui ◽  
Nabil Ali Al-Mekhlafi ◽  
Hussah Abdullah Alshwyeh ◽  
Ahmed Mediani ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Molecular Docking ◽  
Palmitic Acid ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Bioactive Metabolites ◽  
Inhibition Activity ◽  
Chromatography Mass Spectrometry

Fruit of salak (Salaaca zalacca) is traditionally used and commercialized as an antidiabetic agent. However, scientific evidence to prove this folk claim is quite lacking. Therefore, this research was aimed to evaluate the α-glucosidase inhibition activity of S. zalacca fruit and identify the bioactive compounds. The fruits were extracted by different ratios of ethanol and water (0, 20, 40, 60, 80, 100%, v/v) to get E0 (100% water), E20 (20% ethanol), E40 (40% ethanol), E60 (60% ethanol), E80 (80% ethanol), and E100 (100% ethanol) extracts. The extracts obtained were subjected to the α-glucosidase inhibitory assay. Gas chromatography-mass spectrometry- (GC-MS-) based metabolomics approach was used in profiling the bioactive metabolites present in the extracts. Orthogonal partial least square (OPLS) was used to correlate GC-MS data and α-glucosidase assay results to identify the possible chemical markers. All active compounds identified were subjected to molecular docking. The extracts from the S. zalacca fruit showed potent inhibition activity against α-glucosidase. The IC50 values from the α-glucosidase inhibitory assay ranged between 16 and 275 µg/ml. Overall, E60 displayed significantly higher α-glucosidase inhibition activity, while E0 showed the lowest α-glucosidase inhibition activity. Major compounds detected in S. zalacca fruits were sugars, fatty acids, and sterols, including myo-inositol, palmitic acid, stearic acid, and β-sitosterol. Moreover, the results obtained from molecular docking indicated that palmitic acid and β-sitosterol were close to the active side of the enzyme. Some of the residues that interacted include HID295, ASN259, LEU313, LYS125, PHE159, VAL216, PHE178, TYR72, TYR158, HIE315, ARG315, and PHE303. The bioassay result strongly suggests that E60 extract from S. zalacca fruits has potential α-glucosidase inhibitory activity. The hydrophobic compounds, including palmitic acid and β-sitosterol, were found to induce the α-glucosidase inhibition activity.

scholarly journals iMatch: A retention index tool for analysis of gas chromatography–mass spectrometry data

2011 ◽  
Vol 1218 (37) ◽  
pp. 6522-6530 ◽  
Author(s):  
Jun Zhang ◽  
Aiqin Fang ◽  
Bing Wang ◽  
Seong Ho Kim ◽  
Bogdan Bogdanov ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Retention Index ◽  
Mass Spectrometry Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Chromatography Mass Spectrometry

scholarly journals Urinary Volatomic Expression Pattern: Paving the Way for Identification of Potential Candidate Biosignatures for Lung Cancer

Metabolites ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 36
Author(s):  
Khushman Taunk ◽  
Priscilla Porto-Figueira ◽  
Jorge A. M. Pereira ◽  
Ravindra Taware ◽  
Nattane Luíza da Costa ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Fatty Acid Biosynthesis ◽  
Solid Phase ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Support Vector ◽  
Control Group ◽  
Potential Candidate ◽  
Metabolic Pathway Analysis

The urinary volatomic profiling of Indian cohorts composed of 28 lung cancer (LC) patients and 27 healthy subjects (control group, CTRL) was established using headspace solid phase microextraction technique combined with gas chromatography mass spectrometry methodology as a powerful approach to identify urinary volatile organic metabolites (uVOMs) to discriminate among LC patients from CTRL. Overall, 147 VOMs of several chemistries were identified in the intervention groups—including naphthalene derivatives, phenols, and organosulphurs—augmented in the LC group. In contrast, benzene and terpenic derivatives were found to be more prevalent in the CTRL group. The volatomic data obtained were processed using advanced statistical analysis, namely partial least square discriminative analysis (PLS-DA), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) methods. This resulted in the identification of nine uVOMs with a higher potential to discriminate LC patients from CTRL subjects. These were furan, o-cymene, furfural, linalool oxide, viridiflorene, 2-bromo-phenol, tricyclazole, 4-methyl-phenol, and 1-(4-hydroxy-3,5-di-tert-butylphenyl)-2-methyl-3-morpholinopropan-1-one. The metabolic pathway analysis of the data obtained identified several altered biochemical pathways in LC mainly affecting glycolysis/gluconeogenesis, pyruvate metabolism, and fatty acid biosynthesis. Moreover, acetate and octanoic, decanoic, and dodecanoic fatty acids were identified as the key metabolites responsible for such deregulation. Furthermore, studies involving larger cohorts of LC patients would allow us to consolidate the data obtained and challenge the potential of the uVOMs as candidate biomarkers for LC.

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