Integrated Serum and Fecal Metabolomics Study of Collagen-Induced Arthritis Rats and the Therapeutic Effects of the Zushima Tablet

Data-independent acquisition (DIA) in liquid chromatography tandem mass spectrometry (LC-MS/MS) provides more comprehensive untargeted acquisition of molecular data. Here we provide an open-source software pipeline, MS-DIAL, to demonstrate how DIA improves simultaneous identification and quantification of small molecules by mass spectral deconvolution. For reversed phase LC-MS/MS, our program with an enriched LipidBlast library identified total 1,023 lipid compounds from nine algal strains to highlight their chemotaxonomic relationships.

Bile acids are physiological detergents that generate bile flow and facilitate intestinal absorption and transport of lipids, nutrients, and vitamins. Bile acids also are signaling molecules and inflammatory agents that rapidly activate nuclear receptors and cell signaling pathways that regulate lipid, glucose, and energy metabolism. The enterohepatic circulation of bile acids exerts important physiological functions not only in feedback inhibition of bile acid synthesis but also in control of whole-body lipid homeostasis. In the liver, bile acids activate a nuclear receptor, farnesoid X receptor (FXR), that induces an atypical nuclear receptor small heterodimer partner, which subsequently inhibits nuclear receptors, liver-related homolog-1, and hepatocyte nuclear factor 4alpha and results in inhibiting transcription of the critical regulatory gene in bile acid synthesis, cholesterol 7alpha-hydroxylase (CYP7A1). In the intestine, FXR induces an intestinal hormone, fibroblast growth factor 15 (FGF15; or FGF19 in human), which activates hepatic FGF receptor 4 (FGFR4) signaling to inhibit bile acid synthesis. However, the mechanism by which FXR/FGF19/FGFR4 signaling inhibits CYP7A1 remains unknown. Bile acids are able to induce FGF19 in human hepatocytes, and the FGF19 autocrine pathway may exist in the human livers. Bile acids and bile acid receptors are therapeutic targets for development of drugs for treatment of cholestatic liver diseases, fatty liver diseases, diabetes, obesity, and metabolic syndrome.

Background The adaptive immune response in rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. Association of the gut microbiota with various diseases has been reported, though the specific components of the microbiota that affect the host response leading to disease remain unknown. However, there is limited information on the role of gut microbiota in RA. In this study we aimed to define a microbial and metabolite profile that could predict disease status. In addition, we aimed to generate a humanized model of arthritis to confirm the RA-associated microbe. Methods To identify an RA biomarker profile, the 16S ribosomal DNA of fecal samples from RA patients, first-degree relatives (to rule out environment/background as confounding factors), and random healthy non-RA controls were sequenced. Analysis of metabolites and their association with specific taxa was performed to investigate a potential mechanistic link. The role of an RA-associated microbe was confirmed using a human epithelial cell line and a humanized mouse model of arthritis. Results Patients with RA exhibited decreased gut microbial diversity compared with controls, which correlated with disease duration and autoantibody levels. A taxon-level analysis suggested an expansion of rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared with controls. Prediction models based on the random forests algorithm suggested that three genera, Collinsella, Eggerthella, and Faecalibacterium, segregated with RA. The abundance of Collinsella correlated strongly with high levels of alpha-aminoadipic acid and asparagine as well as production of the proinflammatory cytokine IL-17A. A role for Collinsella in altering gut permeability and disease severity was confirmed in experimental arthritis. Conclusions These observations suggest dysbiosis in RA patients resulting from the abundance of certain rare bacterial lineages. A correlation between the intestinal microbiota and metabolic signatures could determine a predictive profile for disease causation and progression. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0299-7) contains supplementary material, which is available to authorized users.