Tariq Saiff Ullah, Syeda Sadiqa Firdous, Hamayun Shaheen, Muhamamd Manzoor, Syed Waseem Gillani, Wayne Thomas Shier, Baber Ali, Tabarak Malik, Sezai Ercisli, Reem M Aljowaie, Mohamed S Elshikh
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引用次数: 0
Abstract
Morels are edible fungi growing naturally in the wild and cultivated for food and medicines worldwide. They have been collected and consumed by people since ancient times. In the present study, fruiting bodies of Morchella elata were collected from the field during the years 2020-22 through consecutive field visits. Identification was carried out through a morpho-anatomical and phylogenetic study that confirmed the collected morel species as Morchella elata. The metabolic analysis was conducted using Ultra High-Performance Liquid Chromatography/Mass Spectrometry (UHPLC/MS) and FTICR/orbitrap techniques. The study revealed the presence of 159 organic compounds and 435 peptide sequences in the ascocarp. Different bioactive and significant compounds have been identified in the fruiting bodies of M. elata. This mushroom is highly nutritious, and the presence of these bioactive compounds contributes to its health benefits, making it a potential functional food in nutraceuticals. From the current study, it is concluded that M. elata is an edible, highly nutritive fungus and contains many bioactive contents. It could be used in the screening of bioactive substances useful in the preparation of anticancer drugs.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.