Metabolite Profiling and Classification of Highbush Blueberry Leaves under Different Shade Treatments

Blueberry belongs to the genus Vaccinium L. in the Ericaceae and is an economically important shrub that produces small berries that are rich in nutrients. There were differences in the appearance of blueberry leaves under different shade treatments. To explore the differences in metabolites in blueberry leaves under different shading treatments, nontargeted liquid chromatography–mass spectrometry (LC–MS) metabonomic analysis was performed. Different shade intensities resulted in significant differences in the contents of metabolites. A total of 6879 known metabolites were detected, including 750 significantly differentially expressed metabolites, including mainly lipids and lipid-like molecules and phenylpropanoid and polyketide superclass members. Based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the flavone and flavonol biosynthesis pathways were the most significantly enriched. The results of this study provide a reference and scientific basis for the establishment of a high-quality and high-yield shaded blueberry cultivation system.

Metabolism modulation in rat tissues in response to point specificity of electroacupuncture

Zusanli (ST36) and Neiguan (PC6) are acupoints along two meridians. To demonstrate point specificity, we investigated the effects of ST36 and PC6 in electroacupuncture (EA)-treated rats. The rats were subjected to sham acupuncture at ST36 without electric stimulation, EA at ST36, or EA at PC6. Heart and stomach tissues were collected for metabolite profiling. Each type of stimulation resulted in a different metabolite composition in the rat heart and stomach tissues. In the heart tissues, EA at ST36 affected a wider range of metabolite pathways than did EA at PC6, whereas similar numbers of metabolites in the stomach tissues were affected by EA at ST36 and PC6. The pathways affected by EA at ST36 differed from those affected by EA at PC6, and a group of common metabolites were reversely regulated by these two acupoints. This study demonstrated point specificity effectively modulated metabolism in rat heart and stomach tissues. The results indicate that heart stimulation may be connected to the stomach through the pericardium meridian (as described in traditional Chinese medicine), explaining why acupuncture applied to the stomach meridian can be an alternative treatment for gastric and heart diseases.

TLC-Based Metabolite Profiling and Bioactivity-Based Scientific Validation for Use of Water Extracts in AYUSH Formulations

We aimed to develop a chromatographic method for scientific validation of water extract of some important Indian traditional plants used in AYUSH-based formulation as immunomodulator and to evaluate their bioactive potential. Fruits of Phyllanthus emblica L. and Piper nigrum L., stem of Tinospora cordifolia (Willd.) Miers, rhizome of Curcuma longa L., leaves of Ocimum sanctum L. and Achillea millefolium L., roots of Withania somnifera L., and stem bark of Azadirachta indica A. Juss. were coarsely powdered and extracted in three different solvents (water, ethanol, and hydroethanol). The antioxidant potential was determined through 1, 1-diphenyl-2-picrylhydrazyl and ferric reducing capacity methods. Thin-layer chromatography (TLC) was carried out for the comparative metabolite profiling of the extracts using toluene, ethyl acetate, and formic acid (5 : 4 : 1, v/v/v) as a solvent system. In vitro immunomodulatory activity of the extracts has been tested on splenocyte proliferation and pinocytic assay. Hydroethanolic extract (HEE) of most of the plant materials has the highest phenolic and flavonoid contents, followed by water extract (WE) and ethanolic extract (EE), whereas the water extracts of most of the plant material showed better antioxidant activity. Almost all extract exhibited splenocyte proliferation and pinocytic activity in a dose-dependent manner. But water extract showed significantly higher splenocyte proliferation and pinocytic activity as compared to the other two extracts. TLC analysis resulted in detection of totally 63 and 56 metabolites at 254 nm and 366 nm, respectively. Through principal component analysis (PCA), it was observed that metabolite pattern of different extracts from same plant materials may be different or similar. This preliminary result can be used for quality evaluation and to develop a synergy-based polyherbal combination of water extracts of selected plant materials.

In vitro Metabolic Stability of Drugs and Applications of LC-MS in Metabolite Profiling

Metabolic stability of a compound is an important factor to be considered during the early stages of drug discovery. If the compound has poor metabolic stability, it never becomes a drug even though it has promising pharmacological characteristics. For example, a drug is quickly metabolized in the body; it does not have sufficient in vivo exposure levels and leads to the production of toxic, non-active or active metabolites. A drug is slowly metabolized in the body it could remain longer periods in the body and lead to unwanted adverse reactions, toxicity or may cause drug interactions. Metabolic stability assay is performed to understand the susceptibility of the compound to undergo biotransformation in the body. Intrinsic clearance of the compound is measured by metabolic stability assays. Different in vitro test systems including liver microsomes, hepatocytes, S9 fractions, cytosol, recombinant expressed enzymes, and cell lines are used to investigate the metabolic stability of drugs. Metabolite profiling is a vital part of the drug discovery process and LC–MS plays a vital role. The development of high-resolution (HR) MS technologies with improved mass accuracy, in conjunction with novel data processing techniques, has significantly improved the metabolite detection and identification process. HR-MS based data acquisition (ion intensity-dependent acquisition, accurate-mass inclusion list-dependent acquisition, isotope pattern-dependent acquisition, pseudo neutral loss-dependent acquisition, and mass defect-dependent acquisition) and data mining techniques (extracted ion chromatogram, product ion filter, mass defect filter, isotope pattern filter, neutral loss filter, background subtraction, and control sample comparison) facilitate the drug metabolite identification process.