Metabolite analysis plays a critical role in understanding phenotypic variations, biochemical processes, and physiological responses in biological systems. Whether through untargeted metabolomic profiling or targeted approaches aimed at quantifying specific or even individual metabolites, accurate detection presents significant analytical challenges due to their vast chemical diversity, low abundance, and complexity of biological matrices. This chemical analytical process encompasses a dynamic workflow that includes sample collection, extraction, enrichment, separation, and detection. Recent advances in nanotechnology offer promising alternatives to support and enhance each stage of this workflow, particularly within mass spectrometry (MS)-based applications. Nanoparticles, due to their high surface area, tunable surface chemistry, and ability to improve sensitivity, have been widely applied to improve sample pretreatment, selective enrichment, separation efficiency, and ionization, ultimately enhancing MS-based metabolites detection. This review provides an updated overview of nanoparticle-assisted strategies throughout the MS-based metabolite analysis workflow. It discusses the different classes of those nanomaterials and their applications across various phases stages, from sample preparation to ionization and detection, supporting analyses that range from untargeted and targeted metabolomics to the detection of individual metabolites. Although the primary focus is on MS-based workflows, we also reviewed nanoparticle-assisted separation strategies coupled with alternative detection platforms, such as optical or electrochemical methods, when these approaches show potential for integration with MS workflows. This inclusion reflects the current gap in literature addressing nanoparticle-assisted separation directly coupled with MS detection systems. These cases highlight underexplored opportunities where nanomaterials could enhance separation prior to MS detection, although further work is needed to ensure compatibility with MS platforms for suitable metabolite analysis. Furthermore, we highlight emerging trends and future perspectives in this evolving field, emphasizing the potential of nanotechnology to overcome current analytical limitations and expand the scope of both metabolomic profiling and focused metabolite analysis.
Gamboa‐Becerra et al. (Sat,) studied this question.