Innovation in identifying metabolites from complex metabolome—Highlights of recent analytical platforms and protocols - Qiu, Shi; Guo, Sifan; Yang, Qiang; Xie, Yiqiang; Tang, Songqi; Zhang, Aihua (Frontiers in Chemistry, 2023)
In 2022, five studies on analytical platforms for identifying metabolites and delineating their contribution by high-throughput mass spectrometry metabolomics were published in Nature Protocols.1-5 These studies have showed metabolic profiling of candidate metabolites as dominant technology enables rapid detection of the metabolic features in the spectral data, which may lead spectral and peak data preprocessing, statistical analysis and functional interpretation. These five publications facilitated the extraction of chemical signals, contributed to identify novel metabolites and identify differential metabolites, and discover new functional biomarkers related metabolites leading to better diagnosis, prognosis and treatment. Future works aimed at developing the integrated strategy for enhancing the accuracy of discovering a list of biological activity metabolites with pathological basis of diseases, could provide a large number of the relatively abundant ions and acquire more reliable identifications, and then shed light on the functional changes of small molecule metabolites more closely. Moreover, it should establish multi-cycle training optimization models of experimental and clinical studies to validate the overall prediction performance of particular metabolite bioactivity and relevant biological significance for disease diagnosis and prognostic treatment that are worthy of further exploration. In the future, the integrated use of computational algorithms, artificial intelligence, and big data mining method will improve the precise identification ability of metabolites for resulting optimization and verification.