Improving data quality in liquid chromatography-mass spectrometry metabolomics of human urine.

Signal variation is a common drawback in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS), mainly due to the complexity of biological matrices and reduced sample preparation, which results in the accumulation of sample components in the column and the ion source. Here we propose a simple, easy to implement approach to improve data quality in untargeted metabolomics by LC-MS. This approach involves the use of a divert valve to direct the column effluent to waste at the beginning of the chromatographic run and during column cleanup and equilibration, in combination with longer column cleanups in between injections. Our approach was tested using urine samples collected from patients after renal transplantation. Analytical responses were contrasted before and after introducing these modifications by analyzing a batch of untargeted metabolomics data. A significant improvement in peak area repeatability was observed for the quality controls, with relative standard deviations (RSDs) for several metabolites decreasing from ∼60% to ∼10% when our approach was introduced. Similarly, RSDs of peak areas for internal standards improved from ∼40% to ∼10%. Furthermore, calibrant solutions were more consistent after introducing these modifications when comparing peak areas of solutions injected at the beginning and the end of each analytical sequence. Therefore, we recommend the use of a divert valve and extended column cleanup as a powerful strategy to improve data quality in untargeted metabolomics, especially for very complex types of samples where minimum sample preparation is required, such as in this untargeted metabolomics study with urine from renal transplanted patients.

Cellular glutathione levels in HL-60 cells during respiratory burst are not correlated with ultra-weak photon emission.

Recently, ultra-weak photon emission (UPE) was developed as a novel tool for measuring oxidative metabolic processes, as its generation is related to reactive oxygen species (ROS). Both an imbalance in ROS or the uncontrolled production of ROS can lead to oxidative stress, which is commonly associated with many diseases. In addition to playing several biological functions, the thiol amino acid glutathione has an important antioxidant function in the body's defense against ROS. Specifically, glutathione is an important endogenous antioxidant that helps maintain oxidant levels. At the cellular level, glutathione is present in its reduced form (GSH) at relatively high concentrations (in the millimolar range) and in its oxidized form (GSSG) at low concentrations (in the micromolar range). Thus, the GSH/GSSG ratio is often used as an indicator of cellular redox state. Here, we used the HL-60 cell line as a model system in order to determine whether UPE is correlated with intracellular GSH and GSSG levels. HL-60 cells were differentiated into neutrophil-like cells and then stimulated to undergo respiratory burst. We then recorded UPE in real time for 9000 seconds and used capillary electrophoresis coupled to mass spectrometry to measure GSH and GSSG levels in cell extracts. We found that although respiratory burst significantly decreased the GSH/GSSG ratio, this change was not significantly correlated with the UPE profile.

Ultra-weak photon emission as a dynamic tool for monitoring oxidative stress metabolism.

In recent years, excessive oxidative metabolism has been reported as a critical determinant of pathogenicity in many diseases. The advent of a simple tool that can provide a physiological readout of oxidative stress would be a major step towards monitoring this dynamic process in biological systems, while also improving our understanding of this process. Ultra-weak photon emission (UPE) has been proposed as a potential tool for measuring oxidative processes due to the association between UPE and reactive oxygen species. Here, we used HL-60 cells as an in vitro model to test the potential of using UPE as readout for dynamically monitoring oxidative stress after inducing respiratory burst. In addition, to probe for possible changes in oxidative metabolism, we performed targeted metabolomics on cell extracts and culture medium. Lastly, we tested the effects of treating cells with the NADPH oxidase inhibitor diphenyleneiodonium chloride (DPI). Our results show that UPE can be used as readout for measuring oxidative stress metabolism and related processes.

Tracking biochemical changes correlated with ultra-weak photon emission using metabolomics.

Ultra-weak photon emission (UPE) is light emitted spontaneously by biological systems without the use of specific luminescent complexes. UPE is emitted in the near-UV/UV-Vis/near-IR spectra during oxidative metabolic reactions; however, the specific pathways involved in UPE remain poorly understood. Here, we used HL-60 cells, a human promyelocytic cell line that is often used to study respiratory burst, as a model system to measure UPE kinetics together with metabolic changes. HL-60 cells were differentiated into neutrophil-like cells by culturing in all-trans-retinoic acid for 7days. We then used a targeted metabolomics approach with capillary electrophoresis-mass spectrometry to profile intracellular metabolites in HL-60 cells and to investigate the biochemical changes based on the measured UPE profile. Our analysis revealed that the levels of specific metabolites, including putrescine, creatine, ß-alanine, methionine, hydroxyproline, serine, and S-adenosylmethionine, were significantly altered in HL-60 cells after inducing respiratory burst. A comparison with recorded UPE data revealed that the changes in putrescine, glutathione, sarcosine, creatine, ß-alanine, methionine, and hydroxyproline levels were inversely correlated with the change in UPE intensity. These results suggest that these metabolic pathways, particular the methionine pathway, may play a role in the observed changes in UPE in HL-60 cells and therefore demonstrate the potential for using UPE to monitor metabolic changes.