Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar stationary phases for untargeted metabolomics by using HILIC columns (neutral and zwitterionic) that have been exploited widely in targeted approaches. To do so, high-resolution mass spectrometry was applied to thoroughly investigate selectivity, repeatability and matrix effect at three pH conditions for 9 classes of polar compounds using 54 authentic standards and plasma matrix. The column performance for utilization in untargeted metabolomics was assessed using plasma samples with diverse phenotypes. Our results indicate that the ZIC-c HILIC column operated at neutral pH exhibited several advantages, including superior performance for different classes of compounds, better isomer separation, repeatability and high metabolic coverage. Regardless of the column type, the retention of inorganic ions in plasma leads to extensive adduct formation and co-elution with analytes, which results in ion-suppression as part of the overall plasma matrix effect. In ZIC-c HILIC, the sodium chloride ion effect was particularly observed for amino acids and amine classes. Successful performance of HILIC for separation of plasma samples with different phenotypes highlights this mode of separation as a valuable approach in global profiling of plasma sample and discovering the metabolic changes associated with health and disease.

The pathological diagnosis of benign and malignant follicular thyroid tumors remains a major challenge using the current histopathological technique. To improve diagnosis accuracy, spatially resolved metabolomics analysis based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique was used to establish a molecular diagnostic strategy for discriminating four pathological types of thyroid tumor. Without any specific labels, numerous metabolite features with their spatial distribution information can be acquired by AFADESI-MSI. The underlying metabolic heterogeneity can be visualized in line with the cellular heterogeneity in native tumor tissue. Through micro-regional feature extraction and in situ metabolomics analysis, three sets of metabolic biomarkers for the visual discrimination of benign follicular adenoma and differentiated thyroid carcinomas were discovered. Additionally, the automated prediction of tumor foci was supported by a diagnostic model based on the metabolic profile of 65 thyroid nodules. The model prediction accuracy was 83.3% when a test set of 12 independent samples was used. This diagnostic strategy presents a new way of performing in situ pathological examinations using small molecular biomarkers and provides a model diagnosis for clinically indeterminate thyroid tumor cases.

Photoactivated chemotherapy agents form a new branch of physically targeted anticancer agents with potentially lower systemic side effects for patients. On the other hand, limited information exists on the intracellular interactions between the photoreleased metal cage and the photoreleased anticancer inhibitor. In this work, we report a new biological study of the known photoactivated compound Ru-STF31 in the glioblastoma cancer cell line, U87MG. Ru-STF31 targets nicotinamide phosphoribosyltransferase (NAMPT), an enzyme overexpressed in U87MG. Ru-STF31 is activated by red light irradiation and releases two photoproducts: the ruthenium cage and the cytotoxic inhibitor STF31. This study shows that Ru-STF31 can significantly decrease intracellular NAD⁺ levels in both normoxic (21% O₂) and hypoxic (1% O₂) U87MG cells. Strikingly, NAD⁺ depletion by light activation of Ru-STF31 in hypoxic U87MG cells could not be rescued by the addition of extracellular NAD⁺. Our data suggest an oxygen-dependent active role of the ruthenium photocage released by light activation.

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/ moieties (MS2 fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRMHR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS2 fragmentation mode based on the measurement of 13C or 15N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of 13C/15N atoms from D-13C6-glucose/L-15N2-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

Endothelial dysfunction, prevalent in cardiovascular diseases (CVDs) and linked to conditions like diabetes, hypertension, obesity, renal failure, or hypercholesterolemia, is characterized by diminished nitric oxide (NO) bioavailability—a key signaling molecule for vascular homeostasis. Current two‐dimensional (2D) in vitro studies on NO synthesis by endothelial cells (ECs) lack the crucial laminar shear stress, a vital factor in modulating the NO‐generating enzyme, endothelial nitric oxide synthase (eNOS), under physiological conditions. Here we developed a tracer‐based metabolomics approach to measure NO‐specific metabolites with mass spectrometry (MS) and show the impact of fluid flow on metabolic parameters associated with NO synthesis using 2D and 3D platforms. Specifically, we tracked the conversion of stable‐isotope labeled NO substrate L‐Arginine to L‐Citrulline and L‐Ornithine to determine eNOS activity. We demonstrated clear responses in human coronary artery endothelial cells (HCAECs) cultured with ¹³ C ₆ , ¹⁵ N ₄ ‐L‐Arginine, and treated with eNOS stimulator, eNOS inhibitor, and arginase inhibitor. Analysis of downstream metabolites, ¹³ C ₆ , ¹⁵ N ₃ L‐Citrulline and ¹³ C ₅ , ¹⁵ N ₂ L‐Ornithine, revealed distinct outcomes. Additionally, we evaluated the NO metabolic status in static 2D culture and 3D microvessel models with bidirectional and unidirectional fluid flow. Our 3D model exhibited significant effects, particularly in microvessels exposed to the eNOS stimulator, as indicated by the ¹³ C ₆ , ¹⁵ N ₃ L‐Citrulline/ ¹³ C ₅ , ¹⁵ N ₂ L‐Ornithine ratio, compared to the 2D culture. The obtained results indicate that the 2D static culture mimics an endothelial dysfunction status, while the 3D model with a unidirectional fluid flow provides a more representative physiological environment that provides a better model to study endothelial dysfunction.

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1^∆/− mouse mutant exhibiting multiple–morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.