ABSTRACT
Introduction: Obesity and diabetes are common chronic metabolic disorders which can cause an imbalance of the intestinal flora and gut-liver metabolism. Several studies have shown that probiotics, including Escherichia coli Nissle 1917 (EcN), promote microbial balance and metabolic health. However, there are no studies on how EcN outer membrane vesicles (EcN-OMVs) influence the intestinal microflora and affect the metabolic disorders of obesity and diabetes. Methods: In this study, we evaluated the effects of EcN-OMVs on high-fat diet (HFD)-induced obesity and HFD + streptozotocin (STZ)-induced diabetes. Results: EcN-OMVs could reduce body weight, decrease blood glucose, and increase plasma insulin in obese mice. Similarly, EcN-OMVs treatment could modify the ratio of Firmicutes/Bacteroidetes in the gut, elevate intestinal short-chain fatty acid (SCFA)-producing flora, and influence the SCFA content of the intestine. Furthermore, the intestinal metabolites ornithine and fumaric acid, hepatic ω-6 unsaturated fatty acids, and SCFAs were significantly increased after administering EcN-OMVs. Discussion: Overall, this study showed that EcN-OMVs might act as post-biotic agents that could modulate gut-liver metabolism and ameliorate the pathophysiology of obesity and diabetes.
ABSTRACT
Polycystic ovary syndrome (PCOS) is a common age-related endocrinopathy that promotes the metabolic disorder of the liver. Growing evidence suggests that the pathophysiology of this disorder is closely associated with the interaction between the liver and its exosome. However, the underlying mechanism of the interactions remains unclear. In this study, we aimed to investigate the metabolite profiles of liver tissues and hepatic exosomes between normal (n = 11) and PCOS (n = 13) mice of young- and middle-age using gas chromatograph-mass spectrometry (GC-MS) based metabolomics analysis. Within the 145 identified metabolites, 7 and 48 metabolites were statistically different (p < 0.05, q < 0.05) in the liver tissue and exosomes, respectively, between PCOS and normal groups. The greater disparity in exosome indicated its potential to reflect the metabolic status of the liver. Based on hepatic exosome metabolome, the downregulations of glycolysis and TCA cycle were related to hepatic pathophysiology of PCOS independent of age. Fatty acids were the preferred substrates in young-age-PCOS liver while amino acids were the main substrates in middle-age-PCOS liver for the processes of gluconeogenesis. Overall, this study enables us to better understand the metabolic status of the PCOS liver at different ages, and exosome metabolomics shows its potential to gain the metabolic insights of parental cell or source organ.
ABSTRACT
Ovarian cancer (OC) is the third most common malignant tumor of women accompanied by alteration of systemic metabolism, yet the underlying interactions between the local OC tissue and other system biofluids remain unclear. In this study, we recruited 17 OC patients, 16 benign ovarian tumor (BOT) patients, and 14 control patients to collect biological samples including ovary plasma, urine, and hair from the same patient. The metabolic features of samples were characterized using a global and targeted metabolic profiling strategy based on Gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) revealed that the metabolites display obvious differences in ovary tissue, plasma, and urine between OC and non-malignant groups but not in hair samples. The metabolic alterations in OC tissue included elevated glycolysis (lactic acid) and TCA cycle intermediates (malic acid, fumaric acid) were related to energy metabolism. Furthermore, the increased levels of glutathione and polyunsaturated fatty acids (linoleic acid) together with decreased levels of saturated fatty acid (palmitic acid) were observed, which might be associated with the anti-oxidative stress capability of cancer. Furthermore, how metabolite profile changes across differential biospecimens were compared in OC patients. Plasma and urine showed a lower concentration of amino acids (alanine, aspartic acid, glutamic acid, proline, leucine, and cysteine) than the malignant ovary. Plasma exhibited the highest concentrations of fatty acids (stearic acid, EPA, and arachidonic acid), while TCA cycle intermediates (succinic acid, citric acid, and malic acid) were most concentrated in the urine. In addition, five plasma metabolites and three urine metabolites showed the best specificity and sensitivity in differentiating the OC group from the control or BOT groups (AUC > 0.90) using machine learning modeling. Overall, this study provided further insight into different specimen metabolic characteristics between OC and non-malignant disease and identified the metabolic fluctuation across ovary and biofluids.
ABSTRACT
Tunable diode laser absorption spectroscopy (TDLAS) is a new method to detect trace-gas qualitatively or quantificationally based on the scan characteristic of the diode laser used to obtain the absorption spectroscopy in the characteristic absorption region It needs to be combined with a long absorption path in the ambient trace-gas measurements. TDLAS is a new trace gas detective method developed with the combination of a tunable diode laser source and a long absorption path; it has significant advantages not only in the sensitivity but also in rapidity of response. It has been widely used in many atmospheric trace-gases detection, ground trace-gas detection and, gas leakage detection. On-line calibrating is necessary to most trace gas monitor, and in the present paper the authors introduced a simple and accurate method, analyzed it in the theory, and proved it's feasibility in the experiment.
