HRMS and molecular networking

Abstract

Objective

High-resolution mass spectrometry (HRMS) represents a significant advancement in analytical toxicology, enabling the acquisition of large datasets with high accuracy. However, the bioinformatic reprocessing of these data can be limited and constrained by commercial software. Molecular networking (MN) uses bioinformatics tools that facilitate the reprocessing of mass spectrometry data through open-access softwares, allowing for the visual grouping of structurally related molecules within samples.

Methods

Using raw data acquired by HRMS/MS, various software programs allow for filtering and reprocessing to generate outputs compatible with graphical softwares. Beyond facilitating the annotation of known compounds within complex samples, this methodology also enables the identification of new metabolites of xenobiotics, presenting many opportunities in clinical and forensic toxicology. Here, we present three original intoxication cases that illustrate the utility of MN to (i) determine which new psychoactive substances have been consumed, (ii) explore the metabolism of the hallucinogenic drug 25E-NBOH, and (iii) visualize complex LC-HR-MS/MS datasets across multiple biological matrices.

Discussion

Molecular networking is a versatile tool that enables the bioinformatic reprocessing of HRMS data in clinical and forensic toxicology. It can also support the study of xenobiotic metabolism through data reprocessing from in vivo or in vitro experiments, making it a preferred tool for such analyses. However, this method is time-intensive and requires sophisticated software, which may limit automation.

Conclusion

Molecular networking is a highly visual tool that allows for semi-quantitative and in-depth analysis of HR-MS/MS data, providing valuable insights for toxicological research.