Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples.

Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

PGC-1α-Dependent Mitochondrial Adaptation Is Necessary to Sustain IL-2-Induced Activities in Human NK Cells.

Human Natural Killer (NK) cells are a specialized heterogeneous subpopulation of lymphocytes involved in antitumor defense reactions. NK cell effector functions are critically dependent on cytokines and metabolic activity. Among various cytokines modulating NK cell function, interleukin-2 (IL-2) can induce a more potent cytotoxic activity defined as lymphokine activated killer activity (LAK). Our aim was to determine if IL-2 induces changes at the mitochondrial level in NK cells to support the bioenergetic demand for performing this enhanced cytotoxic activity more efficiently. Purified human NK cells were cultured with high IL-2 concentrations to develop LAK activity, which was assessed by the ability of NK cells to lyse NK-resistant Daudi cells. Here we show that, after 72 h of culture of purified human NK cells with enough IL-2 to induce LAK activity, both the mitochondrial mass and the mitochondrial membrane potential increased in a PGC-1α-dependent manner. In addition, oligomycin, an inhibitor of ATP synthase, inhibited IL-2-induced LAK activity at 48 and 72 h of culture. Moreover, the secretion of IFN-γ from NK cells with LAK activity was also partially dependent on PGC-1α expression. These results indicate that PGC-1α plays a crucial role in regulating mitochondrial function involved in the maintenance of LAK activity in human NK cells stimulated with IL-2.