Metabolic Perturbation Score-Based Mass Spectrometry Imaging Spatially Resolves a Functional Metabolic Response.

Metabolic perturbation score-based mass spectrometry imaging (MPS-MSI) is proposed to reveal the spatially resolved functional metabolic response associated with disease progression or drug action including metabolism pathways, species, biofunction, or biotransformation. The MPS-MSI enables the exploration of therapeutic or adverse effects, regional heterogeneous responses to drug treatment, possible molecular mechanisms, and even drug potential targets. MPS-MSI was demonstrated to be a promising molecular imaging tool not only for efficacy and safety evaluation but also for molecular mechanism investigation at the early stage of drug research and development.

Ginsenoside 3ß-O-Glc-DM (C3DM) suppressed glioma tumor growth by downregulating the EGFR/PI3K/AKT/mTOR signaling pathway and modulating the tumor microenvironment.

Ginsenosides are the main bioactive constituents of Panax ginseng, which have been broadly studied in cancer treatment. Our previous studies have demonstrated that 3ß-O-Glc-DM (C3DM), a biosynthetic ginsenoside, exhibited antitumor effects in several cancer cell lines with anti-colon cancer activity superior to ginsenoside 20(R)-Rg3 in vivo. However, the efficacy of C3DM on glioma has not been proved yet. In this study, the antitumor activities and underlying mechanisms of C3DM on glioma were investigated in vitro and in vivo. Cell viability, apoptosis, migration, FCM, IHC, RT-qPCR, quantitative proteomics, and western blotting were conducted to evaluate the effect of C3DM on glioma cells. ADP-Glo™ kinase assay was used to validate the interaction between C3DM and EGFR. Co-cultured assays, lactic acid kit, and spatially resolved metabolomics were performed to study the function of C3DM in regulating glioma microenvironment. Both subcutaneously transplanted syngeneic models and orthotopic models of glioma were used to determine the effect of C3DM on tumor growth in vivo. We found that C3DM dose-dependently induced apoptosis, and inhibited the proliferation, migration and angiogenesis of glioma cells. C3DM significantly inhibited tumor growth in both subcutaneous and orthotopic mouse glioma models. Moreover, C3DM attenuated the acidified glioma microenvironment and enhanced T-cell function. Additionally, C3DM inhibited the kinase activity of EGFR and influenced the EGFR/PI3K/AKT/mTOR signaling pathway in glioma. Overall, C3DM might be a promising candidate for glioma prevention and treatment.

Identification of Diagnostic Metabolic Signatures in Thyroid Tumors Using Mass Spectrometry Imaging.

"Gray zone" thyroid follicular tumors are difficult to diagnose, especially when distinguishing between benign follicular thyroid adenoma (FTA) and malignant carcinoma (FTC). Thus, proper classification of thyroid follicular diseases may improve clinical prognosis. In this study, the diagnostic performance of metabolite enzymes was evaluated using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to build a classification model for thyroid follicular tumor characteristics among 24 samples. We analyzed metabolic enzyme marker expression in an independent validation set of 133 cases and further evaluated the potential biological behavior of 19 thyroid borderline lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than FTC (p < 0.001). The metabolic enzyme panel, which included FA synthase and Ca2+-independent PLA2, was further validated in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the ROC, sensitivity, and specificity: 73.6%, 82.1%, and 60.6%, respectively). The findings indicate that AFAIDESI-MSI, in combination with low metabolic enzyme expression, could play a role in the diagnosis of thyroid follicular borderline tumors for strict follow-up.

An Organ-Specific Metabolite Annotation Approach for Ambient Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations of a Whole Mouse Body.

Rapid and accurate metabolite annotation in mass spectrometry imaging (MSI) can improve the efficiency of spatially resolved metabolomics studies and accelerate the discovery of reliable in situ disease biomarkers. To date, metabolite annotation tools in MSI generally utilize isotopic patterns, but high-throughput fragmentation-based identification and biological and technical factors that influence structure elucidation are active challenges. Here, we proposed an organ-specific, metabolite-database-driven approach to facilitate efficient and accurate MSI metabolite annotation. Using data-dependent acquisition (DDA) in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to generate high-coverage product ions, we identified 1620 unique metabolites from eight mouse organs (brain, liver, kidney, heart, spleen, lung, muscle, and pancreas) and serum. Following the evaluation of the adduct form difference of metabolite ions between LC-MS and airflow-assisted desorption electrospray ionization (AFADESI)-MSI and deciphering organ-specific metabolites, we constructed a metabolite database for MSI consisting of 27,407 adduct ions. An automated annotation tool, MSIannotator, was then created to conduct metabolite annotation in the MSI dataset with high efficiency and confidence. We applied this approach to profile the spatially resolved landscape of the whole mouse body and discovered that metabolites were distributed across the body in an organ-specific manner, which even spanned different mouse strains. Furthermore, the spatial metabolic alteration in diabetic mice was delineated across different organs, exhibiting that differentially expressed metabolites were mainly located in the liver, brain, and kidney, and the alanine, aspartate, and glutamate metabolism pathway was simultaneously altered in these three organs. This approach not only enables robust metabolite annotation and visualization on a body-wide level but also provides a valuable database resource for underlying organ-specific metabolic mechanisms.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

Development and validation of a sensitive and reliable targeted metabolomics method for the quantification of cardiovascular disease-related biomarkers in plasma using ultrahigh-performance liquid chromatography-tandem mass spectrometry.

RATIONALE: Cardiovascular disease, as a multifactorial disease caused by genetics and environment, has emerged as a leading cause of mortality. The discovery of metabolic biomarkers for the clinical diagnosis, early warning and elucidation of the molecular pathogenesis of cardiovascular disease, using metabolomics, has attracted broad interest. Therefore, this work aimed to develop a sensitive and reliable targeted metabolomics method for the quantification of cardiovascular disease-related biomarkers in plasma. METHODS: The method was developed and validated using ultrahigh-performance liquid chromatography augmented with tandem mass spectrometry (UHPLC/MS/MS). The LC conditions and MS parameters were optimized using selected reaction monitoring scanning mode to high-throughput and sensitive separation, and could detect 20 metabolic biomarkers in a single experiment. And the linearity, selectivity, accuracy, precision, stability and recovery of the developed method were assessed according to the Bioanalytical Method Validation guidelines of the United States Food and Drug Administration. RESULTS: These quantified metabolic biomarkers are involved in pathways such as aromatic amino acid catabolism (e.g. phenylalanine, tryptophan, tyrosine), trimethylamine N-oxide (TMAO) biosynthesis (e.g. TMAO, choline, carnitine, betaine) and histidine metabolism (e.g. histidine), among others. All analytes exhibited excellent linearities with coefficients of determination greater than 0.99. Accuracies deviated by less than 15% for medium- and high-concentration samples and less than 20% for low-concentration samples, with intra- and inter-day precisions of 1.12-14.12% and 0.30-13.74%, respectively. Recoveries and stabilities also met the analysis requirements of biological samples. CONCLUSIONS: The targeted metabolomics method was shown to have a powerful ability to accurately analyze metabolic biomarkers, thereby providing valuable information for large-scale biomarker validation and clarifying the potential material basis of cardiovascular disease for clinical diagnosis or early warning.

Spatially resolved metabolomics to discover tumor-associated metabolic alterations.

Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.

Molecular Pathological Diagnosis of Thyroid Tumors Using Spatially Resolved Metabolomics.

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.

Rapid Imaging of Unsaturated Lipids at an Isomeric Level Achieved by Controllable Oxidation.

Lipid imaging plays an important role in the research of some diseases, such as cancers. Unsaturated lipids are often present as isomers that can have different functions; however, traditional tandem mass spectrometry imaging (MSI) cannot differentiate between different isomers, which presents difficulties for the pathological study of lipids. Herein, we propose a method for the MSI of the C═C double-bond isomers of unsaturated lipids based on oxidative reactions coupled with air flow-assisted desorption electrospray ionization, which can conveniently achieve rapid MSI of unsaturated lipids at an isomeric level. Using this method, tissue sections can be scanned directly with MSI after only 10 min of accelerated oxidation. This method was used for the imaging of mouse lung cancer tissues, revealing a distributional difference in the unsaturated lipid isomers of normal and pathological regions. Through the MSI of unsaturated lipids at an isomeric level in tissues infected with cancer cells, the regions where the isomers were enriched were exhibited, indicating that these regions were the most concentrated regions of cancer cells. This method provides a convenient platform for studying the functional effects of the isomers of unsaturated lipids in pathological tissues.

Mapping Metabolic Networks in the Brain by Ambient Mass Spectrometry Imaging and Metabolomics.

Metabolic networks and their dysfunction in the brain are closely associated with central nervous function and many psychogenic diseases. Thus, it is of utmost importance to develop a high-throughput imaging method for metabolic network mapping. Here, we developed a metabolic network mapping method to discover the metabolic contexts and alterations with spatially resolved information from the microregion of the brain by ambient-air flow-assisted desorption electrospray ionization mass spectrometry imaging and metabolomics analysis, which can be performed without any chemical derivatization, labels, or complex sample pretreatment. This method can map hundreds of different polar functional metabolites involved in multiple metabolic pathways, including not only neurotransmitters but also purines, organic acids, polyamines, cholines, and carbohydrates, in the rat brain. These high-coverage metabolite profile and microregional distribution information constitute complex networks that regulate advanced functions in the central nervous system. Moreover, this methodology was further used to discover not only the dysregulated metabolites but also the brain microregions involved in the pathology of a scopolamine-treated Alzheimer's model. Furthermore, this methodology was demonstrated to be a powerful visualizing tool that could offer novel insight into the metabolic events and provide spatial information about these events in central nervous system diseases.

Enhanced On-Tissue Chemical Derivatization with Hydrogel Assistance for Mass Spectrometry Imaging.

The improvement of on-tissue chemical derivatization for mass spectrometry imaging (MSI) of low-abundance and/or poorly ionizable functional molecules in biological tissue without delocalization is challenging. Here, we developed a novel hydrogel-assisted chemical derivatization (HCD) approach coupled with airflow-assisted desorption electrospray ionization (AFADESI)-MSI, allowing for enhanced visualization of inaccessible molecules in biological tissues. The derivatization reagent Girard's P (GP) reagent was creatively packaged into a hydrogel to form HCD blocks that have reactivity to carbonyl compounds as well as the feasibility of "cover/uncover" contact mode with tissue sections. The HCD blocks provided a favorable liquid microenvironment for the derivatization reaction and reduced matrix effects from derivatization reagents and tissue without obvious molecular migration, thus improving the derivatization efficiency. With this methodology, unusual carbonyl metabolites, including 166 fatty aldehydes (FALs) and 100 oxo fatty acids (FAs), were detected and visualized in rat brain, kidney, and liver tissue. This study provides a new approach to enhance chemical labeling for in situ tissue submetabolome profiling and improves our knowledge of the molecular histology and complex metabolism of biological tissues.

Strategy for Global Profiling and Identification of 2- and 3-Hydroxy Fatty Acids in Plasma by UPLC-MS/MS.

2-Hydroxy fatty acids (2-OHFAs) and 3-hydroxy fatty acids (3-OHFAs) with the same carbon backbone are isomers, both of which are closely related to diseases involving fatty acid oxidation disorder. However, the comprehensive profiling of 2- and 3-OHFAs remains an ongoing challenge due to their high structure similarity, few structure-informative product ions, and limited availability of standards. Here, we developed a new strategy to profile and identify 2- and 3-OHFAs according to structure-dependent retention time prediction models using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Both accurate MS and MS/MS spectra were collected for peak annotation by comparison with an in-house database of theoretically possible 2- and 3-OHFAs. The structures were further confirmed by the validated structure-dependent retention time prediction models, taking advantage of the correlation between the retention time, carbon chain length and number of double bonds, as well as the hydroxyl position-induced isomeric retention time shift rule. With the use of this strategy, 18 2-OHFAs and 32 3-OHFAs were identified in the pooled plasma, of which 7 2-OHFAs and 20 3-OHFAs were identified for the first time in this work, furthering our understanding of OHFA metabolism. Subsequent quantitation method was developed by scheduled multiple reaction monitoring (MRM) and then applied to investigate the alteration of 2- and 3-OHFAs in esophageal squamous cell carcinoma (ESCC) patients. Finally, a potential biomarker panel consisting of six OHFAs with good diagnostic performance was achieved. Our study provides a new strategy for isomer identification and analysis, showing great potential for targeted metabolomics in clinical biomarker discovery.

Virtual Calibration Quantitative Mass Spectrometry Imaging for Accurately Mapping Analytes across Heterogenous Biotissue.

It is highly challenging to quantitatively map multiple analytes in biotissues without specific chemical labeling. Quantitative mass spectrometry imaging (QMSI) has this potential but still poses technical issues for its variant ionization efficiency across a complicated, heterogeneous biomatrices. Herein, a self-developed air-flow-assisted desorption electrospray ionization (AFADESI) is introduced to present a proof of concept method, virtual calibration (VC) QMSI. This method screens and utilizes analyte response-related endogenous metabolite ions from each mass spectrum as native internal standards (IS). Through machine-learning-based regression and clustering, tissue-specific ionization variation can be automatically recognized, predicted, and normalized region by region or pixel by pixel. Therefore, the quantity of analytes can be accurately mapped across highly structural biosamples including whole body, kidney, brain, tumor, etc. VC-QMSI has the advantages of simple sample preparation without laborious isotopic IS synthesis, extrapolation for those unknown tissues or regions without previous investigation, and automatic spatial recognition without histological guidance. This strategy is suitable for mass spectrometry imaging using a variety of in situ ionization techniques. It is believed that VC-QMSI has wide applicability for drug candidate's discovery, molecular mechanism elucidation, biomarker validation, and clinical diagnosis.

Characterization of two flavonol synthases with iron-independent flavanone 3-hydroxylase activity from Ornithogalum caudatum Jacq.

BACKGROUND: Flavonol synthase (FLS) is the key enzyme responsible for the biosynthesis of flavonols, the most abundant flavonoids, which have diverse pharmaceutical effects. Flavonol synthase has been previously found in other species, but not yet in Ornithogalum caudatum. RESULTS: The transcriptome-wide mining and functional characterisation of a flavonol synthase gene family from O. caudatum were reported. Specifically, a small FLS gene family harbouring two members, OcFLS1 and OcFLS2, was isolated from O. caudatum based on transcriptome-wide mining. Phylogenetic analysis suggested that the two proteins showed the closest relationship with FLS proteins. In vitro enzymatic assays indicated OcFLS1 and OcFLS2 were flavonol synthases, catalysing the conversion of dihydroflavonols to flavonols in an iron-dependent fashion. In addition, the two proteins were found to display flavanone 3ß-hydroxylase (F3H) activity, hydroxylating flavanones to form dihydroflavonols. Unlike single F3H enzymes, the F3H activity of OcFLS1 and OcFLS2 did not absolutely require iron. However, the presence of sufficient Fe2+ was demonstrated to be conducive to successive catalysis of flavanones to flavonols. The qRT-PCR analysis demonstrated that both genes were expressed in the leaves, bulbs, and flowers, with particularly high expression in the leaves. Moreover, their expression was regulated by developmental and environmental conditions. CONCLUSIONS: OcFLS1 and OcFLS2 from O. caudatum were demonstrated to be flavonol synthases with iron-independent flavanone 3-hydroxylase activity.

Development of methionine methylation profiling and relative quantification in human breast cancer cells based on metabolic stable isotope labeling.

Methylation of components involved in one-carbon metabolism is extremely important in cancer; comprehensive studies on methylation are essential and may provide us with a better understanding of tumorigenesis, and lead to the discovery of potential biomarkers. Here, we present an improved methodology for methylated metabolite profiling and its relative quantification in breast cancer cell lines by isotope dilution mass spectrometry based on 13CD3-methionine metabolic labeling using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS). First, all the methylated metabolites related to methionine were first screened and profiled by introducing 13CD3-methionine as the only medium into breast cancer cell growth cultures for both cellular polar metabolites and lipids. In total, we successfully found 20 labeled methylated metabolites and most of them were identified, some of which have not been reported before. We also developed a relative quantification method for all identified methylated metabolites based on isotope dilution mass spectrometry assays. Finally, the developed method was used for different breast cancer cells and mammary epithelial cells. Most methylated metabolites were disrupted in cancer cells. 1-Methyl-nicotinamide was decreased significantly, while trimethylglycine-glutamic acid-lysine and trimethyl-lysine were increased more than five times. This method offers a new insight into the methylation process, with several key pathways and important new metabolites being identified. Further investigation with biological assays should help to reveal the overall methylation metabolic network.

Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry.

Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.

In Situ Hydrogel Conditioning of Tissue Samples To Enhance the Drug's Sensitivity in Ambient Mass Spectrometry Imaging.

Ion suppression from the tissue matrix has a severe effect on the mass spectrometry imaging (MSI) of drugs. This problem hinders further applications of MSI in preclinical drug research and development. In this study, an in situ hydrogel conditioning method was developed to enhance the sensitivity of air-flow-assisted desorption electrospray ionization (AFADESI)-MSI. Instead of the traditional washing or digestion treatment in solvent, this method used a solid phase hydrogel to "wash" tissue sections. It was demonstrated that this in situ hydrogel conditioning method improved the drug signal by as much as 2- to 25-fold in MSI, especially for hydrophobic compounds. Furthermore, the obvious dislocation of analytes was not observed. The evaluation of spatial resolution indicated that the amount of dislocation in tissue sections with the hydrogel process was less than the resolution of AFADESI-MSI. The underlying reasons for the MSI signal enhancement were initially investigated. The decreased signal intensities of choline, betaine, and carnitine and the increased intensities of the [M + H]+/[M + Na]+ and [M + H]+/[M + K]+ ratios for drugs in the mass spectra of pretreated tissues provided evidence that this method can reduce the levels of highly competitive quaternary ammonium and inorganic salts in the tissues. The preformation of a thin liquid film for droplet pickup would also raise the ionization efficiency of drugs. These results demonstrated that this in situ hydrogel conditioning method provides a rapid and feasible approach to improving the sensitivity of ambient MSI for drug mapping in tissues.

Phenolic Acid Profiling, Antioxidant, and Anti-Inflammatory Activities, and miRNA Regulation in the Polyphenols of 16 Blueberry Samples from China.

To investigate the anti-atherosclerosis related mechanism of blueberries, the phenolic acids (PAs) content, antioxidant and anti-inflammatory activities, as well as the microRNA (miRNA) regulation of polyphenol fractions in blueberry samples from China were studied. Sixteen batches of blueberries including 14 commercialized cultivars (Reka, Patriot, Brigitta, Bluecrop, Berkeley, Duke, Darrow, Northland, Northblue, Northcountry, Bluesource, Southgood, O'Neal, and Misty) were used in this study. Seven PAs in the polyphenol fractions from 16 blueberry samples in China were quantified by high performance liquid chromatography/tandem mass spectrometry (HPLC/MS²). The antioxidant activities of blueberry polyphenols were tested by (1,1-diphenyl-2-picrylhydrazyl [DPPH]) assay. The anti-inflammatory (tumor necrosis factor-α [TNF-α] and interleukin-6 [IL-6]) activities of the polyphenol fractions of the blueberries were investigated by using lipopolysaccharide (LPS) induced RAW 264.7 macrophages. The correlation analysis showed that the antioxidant (1,1-diphenyl-2-picrylhydrazyl [DPPH]) and anti-inflammatory (tumor necrosis factor-α [TNF-α] and interleukin-6 [IL-6]) activities of the polyphenol fractions of the blueberries were in accordance with their PA contents. Although the polyphenol-enriched fractions of blueberries could inhibit the microRNAs (miRNAs) (miR-21, miR-146a, and miR-125b) to different extents, no significant contribution from the PAs was observed. The inhibition of these miRNAs could mostly be attributed to the other compounds present in the polyphenol-enriched fraction of the blueberries. This is the first study to evaluate the PAs content, antioxidant and anti-inflammatory activities, and miRNA regulation of Chinese blueberries.

Optimization and Evaluation Strategy of Esophageal Tissue Preparation Protocols for Metabolomics by LC-MS.

Sample preparation is a critical step in tissue metabolomics. Therefore, a comprehensive and systematic strategy for the screening of tissue preparation protocols is highly desirable. In this study, we developed an Optimization and Evaluation Strategy based on LC-MS to screen for a high-extractive efficiency and reproducible esophageal tissue preparation protocol for different types of endogenous metabolites (amino acids, carnitines, cholines, etc.), with a special focus on low-level metabolites. In this strategy, we first selected a large number of target metabolites based on literature survey, previous work in our lab, and known metabolic pathways. For these target metabolites, we tested different solvent extraction methods (biphasic solvent extraction, two-step [TS], stepwise [SW], all-in one [AO]; single-phase solvent extraction, SP) and esophageal tissue disruption methods (homogenized wet tissue [HW], ground wet tissue [GW], and ground dry tissue [GD]). A protocol involving stepwise addition of solvents and a homogenized wet tissue protocol (SWHW) was superior to the others. Finally, we evaluated the stability of endogenous metabolites in esophageal tissues and the sensitivity, reproducibility, and recovery of the optimal protocol. The results proved that the SWHW protocol was robust and adequate for bioanalysis. This strategy will provide important guidance for the standardized and scientific investigation of tissue metabolomics.

Comparison of in vivo immunomodulatory effects of 5-hydroxymethylfurfural and 5, 5'-oxydimethylenebis (2-furfural).

The standard of 5-Hydroxymethylfurfural (5-HMF) existed in dextrose injection as an inevitable by-product during high-temperature setrilization has been included in pharmacopoeias considering its hazardous effects on human health. We found that the concentrations of 5-HMF in some traditional Chinese medicine injections (TCMIs) far exceeded its limit in dextrose injection. Besides, we detected 5, 5'-Oxydimethylenebis (2-furfural) (OMBF) in those TCMIs containing high concentrations of 5-HMF. We investigated the in vivo immunomodulatory effects of 5-HMF and OMBF at three dose levels using the reporter antigen popliteal lymph node assay (RA-PLNA), which allows the straightforward examination and mechanistic study of immunotoxicity of low molecular weight compounds. We found that 5-HMF increased the production of IgG2a and IFN-γ when co-injected with TNP-OVA, indicating its capability of providing a co-stimulatory signal to evoke a typical type-1 immune response. Compared with the 5-HMF, OMBF elevated the production of IgG1, IgG2, IL-4 and IFN-γ in response to both reporter antigens, suggesting that OMBF can act as a neo-antigen or neo-epitope to elicit a mixed type-1 and type-2 immune response. It indicates that both 5-HMF and OMBF have immunosensitizing potential with different mechanisms, and exposure to 5-HMF and OMBF may represent a safety concern for humans.