Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

Abstract

In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.

Novel applications of mass spectrometry‐based metabolomics in herbal medicines and its active ingredients: Current evidence

“…Metabolomics which is defined as the study of small molecules (<1000 Da) produced or consumed within biological systems, is a booming-omics field of post-genomic biological research, to investigate the effects of molecules on biological systems, and provides a holistic approach to explore the molecular changes caused by a variety of factors in the entire organism (Newgard, 2017;Jang, Chen, & Rabinowitz, 2018). Metabolites are regarded as more representative of phenotypes because the faster changes than that of genetic materials, to indicate the current physiological events (Cui, Lu, & Lee, 2018). In essence, metabolomics has been widely employed by the scientific community, and considered to be an extensively used technique for biomarker identification (Guijas et al, 2018a;Mayerle et al, 2018), disease diagnosis (Costello, 2018;Grasso, 2018), novel drug discovery (Wishart, 2016), drug mechanism study (Matsui et al, 2017;Beyer et al, 2018), drug safety, and toxicology evaluation , because it provides highly reliable and repeatable results.…”

Single Spheroid Metabolomics: Optimizing Sample Preparation of Three-Dimensional Multicellular Tumor Spheroids

“…The already-mentioned studies [18][19][20][21][22] with 3D cultures involving LC-MS-based metabolomics workflows, including lipidomics and fluxomics applications utilized washing of the samples and organic solvents (methanol, acetonitrile) with an aqueous proportion for extraction, mostly in cold state. To the best of our knowledge, a thorough evaluation of 3D cancer cell models is still lacking.…”

“…One of the biggest hopes in cancer metabolomics is the discovery of molecular signatures with predictive power in cancer therapy [16]. As a consequence of this renewed interest in metabolism, dedicated workflows were introduced, addressing the needs of preclinical and clinical studies [17][18][19]. Cancer cell model studies required the development and validation of multi-step sample preparation protocols [20].…”

Multiple-biological matrices metabolomics identified new metabolite biomarkers for the precise diagnosis of pancreatic cancer and associated tissue metastasis

“…Glycocholic acid is a secondary bile acid, and particularly high levels of bile acids have been implicated in the pathogenesis of liver diseases 19 . One study suggested that glycocholic acid and taurochenodeoxycholic acid 18 can be used as phenotypic biomarkers in cholangiocarcinoma 20 . In this study, glycocholic acid in plasma was observed to be positively correlated with pancreatic cancer, suggesting that bile acids might also be closely associated with pancreatic cancer.…”