Lactobacillus rhamnosus GG ameliorates hyperuricemia in a novel model.

Hyperuricemia (HUA) is a metabolic syndrome caused by abnormal purine metabolism. Although recent studies have noted a relationship between the gut microbiota and gout, whether the microbiota could ameliorate HUA-associated systemic purine metabolism remains unclear. In this study, we constructed a novel model of HUA in geese and investigated the mechanism by which Lactobacillus rhamnosus GG (LGG) could have beneficial effects on HUA. The administration of antibiotics and fecal microbiota transplantation (FMT) experiments were used in this HUA goose model. The effects of LGG and its metabolites on HUA were evaluated in vivo and in vitro. Heterogeneous expression and gene knockout of LGG revealed the mechanism of LGG. Multi-omics analysis revealed that the Lactobacillus genus is associated with changes in purine metabolism in HUA. This study showed that LGG and its metabolites could alleviate HUA through the gut-liver-kidney axis. Whole-genome analysis, heterogeneous expression, and gene knockout of LGG enzymes ABC-type multidrug transport system (ABCT), inosine-uridine nucleoside N-ribohydrolase (iunH), and xanthine permease (pbuX) demonstrated the function of nucleoside degradation in LGG. Multi-omics and a correlation analysis in HUA patients and this goose model revealed that a serum proline deficiency, as well as changes in Collinsella and Lactobacillus, may be associated with the occurrence of HUA. Our findings demonstrated the potential of a goose model of diet-induced HUA, and LGG and proline could be promising therapies for HUA.

[Comparative study on differences of resin-containing drugs in Dracaena from different appearance based on HS-GC-MS and chemometrics].

Resin-containing drugs in Dracaena from four different appearances were analyzed by headspace sampling-gas chromatography-mass spectrometry(HS-GC-MS) metabolomics technique and hierarchical clustering analysis(HCA) chemometrics method. This study was to analyze differential volatile components in resin-containing drugs in Dracaena from different appearance and metabolic pathways. The results of partial least squares discriminant analysis(PLS-DA) and HCA analysis indicated that there was little difference in volatile components between fiber-rich sample and hollow cork cambium sample, however, the volatile components in the two samples compared with whole body resin-containing sample and resin-secreting aggregated sample had a large metabolic difference. Twenty differential metabolites were screened by VIP and P values of PLS-DA. The content of these differential metabolites was significantly higher in whole body resin-containing sample and resin-secreting aggregated sample than in fiber-rich sample and hollow cork cambium sample. Sixteen significant metabolic pathways were obtained through enrichment analysis(P<0.05), mainly involved in terpenoids biosynthesis and phenylpropanoid metabolism. This result provided a reference for further study of resin formation mechanism of resin-containing drugs in Dracaena from different appearances. At the same time, it also provided a reference for establishing a multi-index quality evaluation system.

A molecular approach to species identification of Chenopodiaceae pollen grains in surface soil.

Pollen identification and classification are important not only for palynologists, but also for systematists and ecologists. Because palynological methods for the identification of pollen in surface soil until now could resolve at best to the generic level, we have developed a molecular approach to species-level identification of Chenopodiaceae pollen in surface soils. Surface soil samples were collected in the central area of Junggar Desert Basin, Xinjiang, China. Fresh leaves of 19 Chenopodiaceae species were sampled for DNA sequencing, establishing a database of internal transcribed spacer (ITS) regions of nuclear ribosomal DNA for Chenopodiaceae. Individual chenopod pollen grains in a soil sample were separated from the soil and the ITS1 region of each pollen grain was amplified using nested PCR and sequenced. By comparing the amplified ITS1 sequences to those in the Chenopodiaceous database, we identified the pollen in the soil samples to the level of species. The new method provides a technical reference for species identification of soil surface pollen for other families. This work is necessary for further efforts to interpret the relationship of surface soil pollen to vegetation characteristics. It also has significant potential for enhancing the ability to identify pollen in clinical airborne allergen or criminological studies.