Nuclear magnetic resonance-based plasma metabolomics revealed the protective effect of tea polyphenols on sulfur mustard-induced injury in rats

Optimization of metabolomics pretreatment method of cholangiocarcinoma cells based on ultrahigh performance liquid chromatography coupled with mass spectrometry

Metabolomics intends to maximize the quantity of available metabolites for the global metabolome, which largely depends on sample pretreatment protocols. However, there are few studies that comprehensively examined the effects of extraction and reconstitution solvents on metabolome coverage of adherent mammalian cells. In this study, the human cholangiocarcinoma TFK-1 cells were chosen as a cell model, and eight extraction solvents and five reconstitution solvents were used for the pretreatment based on ultrahigh performance liquid chromatography coupled with mass spectrometry (UPLC/MS). The coverage, reproducibility, and stability of the data were norms to evaluate the effectiveness of different extraction solvents and reconstitution solvents. Based on the number of metabolites, the mean Euclidean distance (EDMEAN) in the principal component analysis (PCA) 3D score plots and the relative standard deviation (RSD) distribution of metabolites, it was demonstrated that MeOH-CHCl3-H2O (8:1:1, v/v/v) was the optimal extraction solvent and MeOH-H2O (1:1, v/v) or H2O was superior to other reconstitution solvents for RP column analysis, and the extraction solvent MeOH-ACN-H2O (2:2:1, v/v/v) and the reconstitution solvents ACN-H2O (4:1, v/v) or MeOH-H2O (1:1, v/v) provide the best performance for HILIC column analysis. The optimized pretreatment methods explored in this study expand the coverage of polar and non-polar metabolites and improve the reproducibility and stability of the metabolic data, which can be applied to UPLC/MS-based global metabolomics study on cholangiocarcinoma cells, potentially providing better extraction solvents and reconstitution solvents for other adherent mammalian cells with similar chemical and physical properties.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Metabolomic profiling of cerebrospinal fluid reveals an early diagnostic model for central nervous system involvement in acute lymphoblastic leukaemia

The pathogenesis of central nervous system involvement (CNSI) in patients with acute lymphoblastic leukaemia (ALL) remains unclear and a robust biomarker of early diagnosis is missing. An untargeted cerebrospinal fluid (CSF) metabolomics analysis was performed to identify independent risk biomarkers that could diagnose CNSI at the early stage. Thirty-three significantly altered metabolites between ALL patients with and without CNSI were identified, and a CNSI evaluation score (CES) was constructed to predict the risk of CNSI based on three independent risk factors (8-hydroxyguanosine, l-phenylalanine and hypoxanthine). This predictive model could diagnose CNSI with positive prediction values of 95.9% and 85.6% in the training and validation sets respectively. Moreover, CES score increased with the elevated level of central nervous system (CNSI) involvement. In addition, we validated this model by tracking the changes in CES at different stages of CNSI, including before CNSI and during CNSI, and in remission after CNSI. The CES showed good ability to predict the progress of CNSI. Finally, we constructed a nomogram to predict the risk of CNSI in clinical practice, which performed well compared with observed probability. This unique CSF metabolomics study may help us understand the pathogenesis of CNSI, diagnose CNSI at the early stage, and sequentially achieve personalized precision treatment.

Evidence for the systemic diffusion of (2-chloroethyl)-ethyl-sulfide, a sulfur mustard analog, and its deleterious effects in brain

Sulfur mustard, a chemical warfare agent known to be a vesicant of skin, readily diffuses in the blood stream and reaches internal organs. In the present study, we used the analog (2-chloroethyl)-ethyl-sulfide (CEES) to provide novel data on the systemic diffusion of vesicants and on their ability to induce brain damage, which result in neurological disorders. SKH-1 hairless mice were topically exposed to CEES and sacrificed at different time until 14 days after exposure. A plasma metabolomics study showed a strong systemic impact following a self-protection mechanism to alleviate the injury of CEES exposure. This result was confirmed by the quantification of specific biomarkers in plasma. Those were the conjugates of CEES with glutathione (GSH-CEES), cysteine (Cys-CEES) and N-acetyl-cysteine (NAC-CEES), as well as the guanine adduct (N7Gua-CEES). In brain, N7Gua-CEES could be detected both in DNA and in organ extracts. Similarly, GSH-CEES, Cys-CEES and NAC-CEES were present in the extracts until day14. Altogether, these results, based on novel exposure markers, confirm the ability of vesicants to induce internal damage following dermal exposure. The observation of alkylation damage to glutathione and DNA in brain provides an additional mechanism to the neurological insult of SM.