Enhancing Metabolome Annotation by Electron Impact Excitation of Ions from Organics-Molecular Networking.

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is widely used in untargeted metabolomics, but large-scale and high-accuracy metabolite annotation remains a challenge due to the complex nature of biological samples. Recently introduced electron impact excitation of ions from organics (EIEIO) fragmentation can generate information-rich fragment ions. However, effective utilization of EIEIO tandem mass spectrometry (MS/MS) is hindered by the lack of reference spectral databases. Molecular networking (MN) shows great promise in large-scale metabolome annotation, but enhancing the correlation between spectral and structural similarity is essential to fully exploring the benefits of MN annotation. In this study, a novel approach was proposed to enhance metabolite annotation in untargeted metabolomics using EIEIO and MN. MS/MS spectra were acquired in EIEIO and collision-induced dissociation (CID) modes for over 400 reference metabolites. The study revealed a stronger correlation between the EIEIO spectra and metabolite structure. Moreover, the EIEIO spectral network outperformed the CID spectral network in capturing structural analogues. The annotation performance of the structural similarity network for untargeted LC-MS/MS was evaluated. For the spiked NIST SRM 1950 human plasma, the annotation coverage and accuracy were 72.94 and 74.19%, respectively. A total of 2337 metabolite features were successfully annotated in NIST SRM 1950 human plasma, which was twice that of LC-CID MS/MS. Finally, the developed method was applied to investigate prostate cancer. A total of 87 significantly differential metabolites were annotated. This study combining EIEIO and MN makes a valuable contribution to improving metabolome annotation.

Deep Annotation of Hydroxycinnamic Acid Amides in Plants Based on Ultra-High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry and Its In Silico Database.

Hydroxycinnamic acid amides (HCAAs), diversely distributed secondary metabolites in plants, play essential roles in plant growth and developmental processes. Most current approaches can be used to analyze a few known HCAAs in a given plant. A novel method for comprehensive detection of plant HCAAs is urgently needed. In this study, a deep annotation method of HCAAs was proposed on the basis of ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) and its in silico database of HCAAs. To construct an in silico UHPLC-HRMS HCAAs database, a total of 846 HCAAs were generated from the most common phenolic acid and polyamine/aromatic monoamine substrates according to possible biosynthesis reactions, which represent the structures of plant-specialized HCAAs. The characteristic MS/MS fragmentation patterns of HCAAs were extracted from reference mixtures. Four quantitative structure-retention relationship (QSRR) models were developed to predict retention times of mono-trans-HCAAs (aromatic amines conjugates), mono-trans-HCAAs (aliphatic amines conjugates), bis-HCAAs, and tris-HCAAs. The developed method was applied for identifying HCAAs in seeds (maize, wheat, and rice), roots (rice), and leaves (rice and tobacco). A total of 79 HCAAs were detected: 42 of them were identified in these plants for the first time, and 20 of them have never been reported to exist in plants. The results showed that the developed method can be used to identify HCAAs in a plant without prior knowledge of HCAA distributions. To the best of our knowledge, it is the first UHPLC-HRMS database developed for effective deep annotation of HCAAs from nontargeted UHPLC-HRMS data. It is useful for the identification of novel HCAAs in plants.

Propofol Promotes Activity and Tumor-Killing Ability of Natural Killer Cells in Peripheral Blood of Patients with Colon Cancer.

BACKGROUND We investigated the effect of propofol on activities and tumor-killing ability of natural killer (NK) cells in patients with colon cancer. MATERIAL AND METHODS Twenty colon cancer patients and 20 healthy subjects were included. Peripheral blood (5 ml) was collected from all patients and healthy subjects. NK cells in peripheral blood were separated by negative screening using immunomagnetic beads. Flow cytometry was used to determine expression of activated receptors, inhibitory receptors, killing effector molecules, and proliferation-associated markers on NK cell surfaces. After in vitro treatment with propofol for 24 h, expression of activated receptors, inhibitory receptors, killing effector molecules, and proliferation-associated markers on NK cell surfaces was examined again. In addition, the tumor-killing effect of NK cells was studied by co-culture with K562 cells or colon cancer SW620 cells at a ratio of 1: 1. RESULTS The number of NK cells in peripheral blood from colon cancer patients was increased compared with healthy subjects, but activities and proliferation ability of the NK cells were decreased. The tumor-killing effect of NK cells isolated from colon cancer patients was decreased. Of note, propofol promoted activation of NK cells from colon cancer patients. In addition, propofol increased expression of tumor-killing effector molecules by NK cells and the proliferation ability of NK cells. Propofol also enhanced the killing effect of NK cells on colon cancer cells. CONCLUSIONS The present study demonstrates that propofol promotes the activity and tumor-killing ability of NK cells in peripheral blood of patients with colon cancer.