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The gut microbiota plays a central role in human health by enzymatically degrading dietary fiber and concomitantly excreting short chain fatty acids that are associated with manifold health benefits. The polysaccharide xylan is abundant in dietary fiber but non-carbohydrate decorations hinder efficient cleavage by glycoside hydrolases (GHs) and need to be addressed by carbohydrate esterases (CEs). Enzymes from carbohydrate esterase families 1 and 6 (CE1 &amp; 6) perform key roles in xylan degradation by removing feruloyl and acetate decorations, yet little is known about these enzyme families especially with regards to their diversity in activity. Bacteroidetes bacteria are dominant members of the microbiota and often encode their carbohydrate-active enzymes in multi-gene polysaccharide utilization loci (PULs). Here we present the characterization of three CEs found in a PUL encoded by the gut Bacteroidete Dysgonomonas mossii. We demonstrate that the CEs are functionally distinct, with one highly efficient CE6 acetyl esterase and two CE1 enzymes with feruloyl esterase activities. One multidomain CE1 enzyme contains two CE1 domains an N-terminal domain feruloyl esterase, and a C-terminal domain with minimal activity on model substrates. We present the structure of the C-terminal CE1 domain with the carbohydrate binding module that bridges the two CE1 domains, as well as a complex of the same protein fragment with methyl ferulate. The investment of D. mossii in producing multiple CEs suggests that improved accessibility of xylan for GHs as well as cleavage of covalent polysaccharide-polysaccharide and lignin-polysaccharide bonds are important enzyme activities in the gut environment.Hepatic glycogen metabolism is impaired in diabetes. We previously demonstrated that strategies to increase liver glycogen content in a high-fat-diet mouse model of obesity and insulin resistance led to a reduction in food intake and ameliorated obesity and glucose tolerance. These effects were accompanied by a decrease in insulin levels, but whether this decrease contributed to the phenotype observed in this animal was unclear. Here we sought to evaluate this aspect directly, by examining the long-term effects of increasing liver glycogen in an animal model of insulin-deficient and monogenic diabetes, namely the Akita mouse, which is characterized by reduced insulin production. We crossed Akita mice with animals overexpressing protein targeting to glycogen (PTG) in the liver to generate Akita mice with increased liver glycogen content (Akita-PTGOE). Akita-PTGOE animals showed lower glycemia, lower food intake, and decreased water consumption and urine output compared with Akita mice. Furthermore, Akita-PTGOE mice showed a restoration of the hepatic energy state and a normalization of gluconeogenesis and glycolysis back to non-diabetic levels. Moreover, hepatic lipogenesis, which is reduced in Akita mice, was reverted in Akita-PTGOE animals. These results demonstrate that strategies to increase liver glycogen content lead to the long-term reduction of the diabetic phenotype, independently of circulating insulin.Bone Morphogenetic Proteins (BMPs) secreted by a variety of cell types are known to play essential roles in cell differentiation and matrix formation in bone, cartilage, muscle, blood vessels, and neuronal tissues. BMPs activate intracellular effectors via C-terminal phosphorylation of Smad1, 5 and 9, which relay the signaling by forming a complex with Smad4 and translocate to the nucleus for transcriptional activation. Smad6 inhibits BMP signaling through diverse mechanisms operative at the membrane, cytosolic and nuclear levels. However, the mechanistic underpinnings of Smad6 functional diversity remain unclear. Here, using biochemical approach and cell differentiation systems, we report a cytosolic mechanism of action for Smad6 that requires arginine methylation at R81 and functions through association with Smad1 and interference with the formation of Smad1/Smad4 complexes. By mutating the methylated arginine residue, R81, and by silencing expression of protein arginine methyltransferase 1 (PRMT1), we show that PRMT1 catalyzes R81 methylation of Smad6 upon BMP treatment; R81 methylation subsequently facilitates Smad6 interaction with the phosphorylated active Smad1; and R81 methylation facilitates Smad6-mediated interruption of Smad1/Smad4 complex formation and nuclear translocation. Furthermore, Smad6 wild type but not the methylation-deficient R81A mutant inhibited BMP-responsive transcription, attenuated BMP-mediated osteogenic differentiation and antagonized BMP-mediated inhibition of cell invasion. Taken together our results suggest that R81 methylation plays an essential role in Smad6-mediated inhibition of BMP responses.Tissue geometry is an important influence on the evolution of many biological tissues. The local curvature of an evolving tissue induces tissue crowding or spreading, which leads to differential tissue growth rates, and to changes in cellular tension, which can influence cell behaviour. Here, we investigate how directed cell motion interacts with curvature control in evolving biological tissues. Directed cell motion is involved in the generation of angled tissue growth and anisotropic tissue material properties, such as tissue fibre orientation. We develop a new cell-based mathematical model of tissue growth that includes both curvature control and cell guidance mechanisms to investigate their interplay. The model is based on conservation principles applied to the density of tissue synthesising cells at or near the tissue's moving boundary. The resulting mathematical model is a partial differential equation for cell density on a moving boundary, which is solved numerically using a hybrid front-tracking method called the cell-based particle method. [https://www.selleckchem.com/products/pf-06826647.html selleck chemicals llc] The inclusion of directed cell motion allows us to model new types of biological growth, where tangential cell motion is important for the evolution of the interface, or for the generation of anisotropic tissue properties. We illustrate such situations by applying the model to simulate both the resorption and infilling components of the bone remodelling process, and to simulate root hair growth. We also provide user-friendly MATLAB code to implement the algorithms.