The role of Galactose in human health and disease

Green tea polyphenols modify gut-microbiota dependent metabolisms of energy, bile constituents and micronutrients in female Sprague-Dawley rats

Our recent metagenomics analysis has uncovered remarkable modifying effects of green tea polyphenols (GTP) on gut-microbiota community structure and energy conversion related gene orthologs in rats. How these genomic changes could further influence host health is still unclear. In this work, the alterations of gut-microbiota dependent metabolites were studied in the GTP-treated rats. Six groups of female SD rats (n=12/group) were administered drinking water containing 0%, 0.5%, and 1.5% GTP (wt/vol). Their gut contents were collected at 3 and 6 months and were analyzed via high performance liquid chromatography (HPLC) and gas chromatography (GC)-mass spectrometry (MS). GC-MS based metabolomics analysis captured 2668 feature, and 57 metabolites were imputatively from top 200 differential features identified via NIST fragmentation database. A group of key metabolites were quantitated using standard calibration methods. Compared with control, the elevated components in the GTP-treated groups include niacin (8.61-fold), 3-phenyllactic acid (2.20-fold), galactose (3.13-fold), mannose (2.05-fold), pentadecanoic acid (2.15-fold), lactic acid (2.70-fold), and proline (2.15-fold); the reduced components include cholesterol (0.29-fold), cholic acid (0.62-fold), deoxycholic acid (0.41-fold), trehalose (0.14-fold), glucose (0.46-fold), fructose (0.12-fold), and alanine (0.61-fold). These results were in line with the genomic alterations of gut-microbiome previously discovered by metagenomics analysis. The alterations of these metabolites suggested the reduction of calorific carbohydrates, elevation of vitamin production, decreases of bile constituents, and modified metabolic pattern of amino acids in the GTP-treated animals. Changes in gut-microbiota associated metabolism may be a major contributor to the anti-obesity function of GTP.

First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene

GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.