Metabolomics of natural samples: A tutorial review on the latest technologies

Abstract

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early‐career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early‐career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

A ternary correlation multi‐symptom network strategy based on in vivo chemical profile identification and metabolomics to explore the molecular basis of Ephedra herb against viral pneumonia

“…Molecular Networking (MN) identified the compound based on the similarity of MS/MS fragmentation and clustering of precursor ions (MS1) into clusters via Global Nature Products Social Molecular Networking (GNPS) [28]. The emergence of MN‐combined metabolomics has facilitated the rapid separation and identification of complex components in TCM, providing an effective technical approach for this field [29, 30]. The metDNA is also an analytical strategy for metabolite identification by implementing a recursive algorithm based on a metabolic reaction network (MRN) [31].…”