The molecular basis of cereal mixed-linkage ß-glucan utilization by the human gut bacterium Segatella copri.

Mixed-linkage ß(1,3)/ß(1,4)-glucan (MLG) is abundant in the human diet through the ingestion of cereal grains and is widely associated with healthful effects on metabolism and cholesterol levels. MLG is also a major source of fermentable glucose for the human gut microbiota (HGM). Bacteria from the family Prevotellaceae are highly represented in the HGM of individuals who eat plant-rich diets, including certain indigenous people and vegetarians in postindustrial societies. Here, we have defined and functionally characterized an exemplar Prevotellaceae MLG polysaccharide utilization locus (MLG-PUL) in the type-strain Segatella copri (syn. Prevotella copri) DSM 18205 through transcriptomic, biochemical, and structural biological approaches. In particular, structure-function analysis of the cell-surface glycan-binding proteins and glycoside hydrolases of the S. copri MLG-PUL revealed the molecular basis for glycan capture and saccharification. Notably, syntenic MLG-PULs from human gut, human oral, and ruminant gut Prevotellaceae are distinguished from their counterparts in Bacteroidaceae by the presence of a ß(1,3)-specific endo-glucanase from glycoside hydrolase family 5, subfamily 4 (GH5_4) that initiates MLG backbone cleavage. The definition of a family of homologous MLG-PULs in individual species enabled a survey of nearly 2000 human fecal microbiomes using these genes as molecular markers, which revealed global population-specific distributions of Bacteroidaceae- and Prevotellaceae-mediated MLG utilization. Altogether, the data presented here provide new insight into the molecular basis of ß-glucan metabolism in the HGM, as a basis for informing the development of approaches to improve the nutrition and health of humans and other animals.

SACCHARIS v2: Streamlining Prediction of Carbohydrate-Active Enzyme Specificities Within Large Datasets.

Carbohydrates are chemically and structurally diverse, composed of a wide array of monosaccharides, stereochemical linkages, substituent groups, and intermolecular associations with other biological molecules. A large repertoire of carbohydrate-active enzymes (CAZymes) and enzymatic activities are required to form, dismantle, and metabolize these complex molecules. The software SACCHARIS (Sequence Analysis and Clustering of CarboHydrate Active enzymes for Rapid Informed prediction of Specificity) provides a rapid, easy-to-use pipeline for the prediction of potential CAZyme function in new datasets. We have updated SACCHARIS to (i) simplify its installation by re-writing in Python and packaging for Conda; (ii) enhance its usability through a new (optional) interactive GUI; and (iii) enable semi-automated annotation of phylogenetic tree output via a new R package or the commonly-used webserver iTOL. Significantly, SACCHARIS v2 has been developed with high-throughput omics in mind, with pipeline automation geared toward complex (meta)genome and (meta)transcriptome datasets to reveal the total CAZyme content ("CAZome") of an organism or community. Here, we outline the development and use of SACCHARIS v2 to discover and annotate CAZymes and provide insight into complex carbohydrate metabolisms in individual organisms and communities.