Background. Irritable bowel syndrome (IBS) is a common chronic functional gastrointestinal disease accompanied by changes in intestinal microecology. This study investigated the relationship between gut microbiota and disease severity in patients with irritable bowel syndrome (IBS). Methods. An observational study was performed on 60 IBS patients (study group) and 20 healthy controls admitted to our hospital from January 2013 to December 2014. Fecal samples were taken after admission to measure intestinal flora including Bifidobacterium, Lactobacillus, Enterobacter, and Enterococcus, and patient blood was collected to determine serum D-lactate and diamine oxidase (DAO) levels. The gut microbiota and serum markers of the two groups were analyzed. The correlation of gut microbiota index levels and serum markers with disease severity, as well as the correlation between gut microbiota index levels and serum markers, were analyzed. Results. The levels of intestinal Lactobacillus and Bifidobacterium were lower, while the levels of Enterococcus and Enterobacter and serum D-lactate were higher in the study group than those in the control group. The levels of intestinal Lactobacillus and Bifidobacterium were lower, while the levels of Enterococcus and Enterobacter, serum D-lactate, and DAO were higher in patients with moderate IBS than those in patients with mild IBS. The levels of intestinal Lactobacillus and Bifidobacterium were lower in patients with severe IBS than those with moderate IBS, while the levels of Enterococcus and Enterobacter, serum D-lactate, and DAO were higher in patients with severe IBS. There was a significant negative correlation between the levels of Lactobacillus and Bifidobacterium and disease severity and a significant positive correlation between the levels of Enterococcus and Enterobacter, D-lactate, and DAO and disease severity. There was a significant negative correlation between the levels of Lactobacillus and Bifidobacterium and serum D-lactate and DAO, while there was a significant positive correlation between the levels of Enterococcus and Enterobacter and serum D-lactate and DAO ( P < 0.05 ). Conclusion. Intestinal flora, D-lactate, and DAO were abnormal in IBS patients, and intestinal flora was closely correlated with disease severity, D-lactate, and DAO levels.

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Arctigenin is a phenylpropanoid dibenzylbutyro lactone lignan compound with multiple biological functions. Previous studies have shown that arctigenin have neuroprotective effects in Alzheimer’s disease (AD) models both in vivo and in vitro; however, its metabolism in vivo has not been studied. Most traditional analytical methods only partially characterize drug metabolite prototypes, so there is an urgent need for a research strategy that can fully characterize drug metabolites. In the present study, ions fishing with a serial five-membered lactone ring as a fishhook strategy based on ultrahigh-performance liquid chromatography-Q-Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap MS) was utilised to characterise the metabolism of arctigenin, and the establishment of this strategy also solved the challenge of creating a comprehensive metabolic profile of neolignan. Based on the proposed strategy, a total of 105 metabolites were detected and characterised, 76 metabolites of which were found in rats and 49 metabolites in liver microsomes. These metabolites were postulated to be produced through oxidation, reduction, hydrolysis, and complex reactions. Subsequently, network pharmacology was utilized to elucidate the mechanism of arctigenin and its main metabolites against Alzheimer’s disease, screening 381 potential targets and 20 major signaling pathways. The study on the comprehensive metabolism of arctigenin provides a holistic metabolic profile, which will help to better understand the mechanism of arctigenin in the treatment of Alzheimer’s disease (AD) and also provide a basis for the safe administration of arctigenin.

Mangiferin, a natural flavonoid compound with multiple biological activities (e.g., anti-inflammatory, anti-oxidant, anti-diabetic, and anti-tumor), has gained increased research interest in recent years. Nevertheless, the metabolic processing of mangiferin has not been fully investigated. In this study, a rapid and efficient analytical strategy named “Drug Metabolite Clusters” was applied for comprehensive profiling of mangiferin metabolites in rat plasma, urine, and feces samples in vivo following oral administration and liver microsomes in vitro. First, the biological samples were pretreated with methanol, acetonitrile, and solid phase extraction (SPE) for further liquid chromatography–mass spectrometry (LC–MS) analysis. Second, the raw data were acquired using ultra-high performance liquid chromatography quadrupole exactive orbitrap high-resolution mass spectrometry (UHPLC-Q-Exactive Orbitrap HRMS) under the positive and negative full-scan/dd MS2 modes. Third, mangiferin and its basic metabolites (norathyriol, trihydroxyxanthone, and dihydroxyxanthone) were selected as mangiferin metabolite cluster centers by referring to the relevant literature. Subsequently, according to the pyrolysis law of mass spectrometry, literature reports, and reference material comparison, especially the diagnostic product ions (DPIs), the candidate metabolites were accurately preliminarily identified, and mangiferin metabolite clusters based on metabolite cluster center changes were formed. As a result, a total of 67 mangiferin metabolites (mangiferin included) were detected, including 29 in plasma, 48 in urine, 12 in feces, and 6 in liver microsomes. Among them, trihydroxyxanthones were first detected in rat urine samples after oral mangiferin. We found that mangiferin mainly underwent deglucosylation, dehydroxylation, methylation, glucuronidation, sulfation, and other composite reactions in rats. Herein, we have elucidated the metabolites and metabolic pathways of mangiferin in vivo and in vitro, which provided an essential theoretical basis for further pharmacological studies of mangiferin and a comprehensive research method for the identification of drug metabolites.