The translational roles of the Shine-Dalgarno sequence, the initiation codon, the space between them, and the second codon have been studied. The Shine-Dalgarno sequence UAAGGAGG initiated translation roughly four times more efficiently than did the shorter AAGGA sequence. Each Shine-Dalgarno sequence required a minimum distance to the initiation codon in order to drive translation; spacing, however, could be rather long. Initiation at AUG was more efficient than at GUG or UUG at each spacing examined; initiation at GUG was only slightly better than UUG. Translation was also affected by residues 3' to the initiation codon. The second codon can influence the rate of initiation, with the magnitude depending on the initiation codon. The data are consistent with a simple kinetic model in which a variety of rate constants contribute to the process of translation initiation.

OBJECTIVEExcessive endogenous glucose production contributes to fasting hyperglycemia in diabetes. This effect stems from inept insulin suppression of hepatic gluconeogenesis. To understand the underlying mechanisms, we studied the ability of forkhead box O6 (FoxO6) to mediate insulin action on hepatic gluconeogenesis and its contribution to glucose metabolism.RESEARCH DESIGN AND METHODSWe characterized FoxO6 in glucose metabolism in cultured hepatocytes and in rodent models of dietary obesity, insulin resistance, or insulin-deficient diabetes. We determined the effect of FoxO6 on hepatic gluconeogenesis in genetically modified mice with FoxO6 gain- versus loss-of-function and in diabetic db/db mice with selective FoxO6 ablation in the liver.RESULTSFoxO6 integrates insulin signaling to hepatic gluconeogenesis. In mice, elevated FoxO6 activity in the liver augments gluconeogenesis, raising fasting blood glucose levels, and hepatic FoxO6 depletion suppresses gluconeogenesis, resulting in fasting hypoglycemia. FoxO6 stimulates gluconeogenesis, which is counteracted by insulin. Insulin inhibits FoxO6 activity via a distinct mechanism by inducing its phosphorylation and disabling its transcriptional activity, without altering its subcellular distribution in hepatocytes. FoxO6 becomes deregulated in the insulin-resistant liver, accounting for its unbridled activity in promoting gluconeogenesis and correlating with the pathogenesis of fasting hyperglycemia in diabetes. These metabolic abnormalities, along with fasting hyperglycemia, are reversible by selective inhibition of hepatic FoxO6 activity in diabetic mice.CONCLUSIONSOur data uncover a FoxO6-dependent pathway by which the liver orchestrates insulin regulation of gluconeogenesis, providing the proof-of-concept that selective FoxO6 inhibition is beneficial for curbing excessive hepatic glucose production and improving glycemic control in diabetes.

Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). The impact of this method, especially for heterogeneous human populations, is to reduce the false-positive rate, inflate other spuriously small p values, and have little impact on the p values associated with true positive loci. Thus, it highlights true positives by downplaying false positives. We perform a GWA by matching Americans with type 1 diabetes (T1D) to controls from Germany. Despite the complex study design, these analyses identify numerous loci known to confer risk for T1D.

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising SNPs are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.

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Background: Hypertriglyceridemia is the most common lipid disorder with incompletely understood mechanisms. Results: ATF4 deficiency attenuates lipogenesis in the liver and protects against high fructose-induced hypertriglyceridemia in mice. Conclusion: ATF4 plays a pivotal role in regulating hepatic lipid metabolism. Significance: ATF4 is a contributing factor for the pathogenesis of hypertriglyceridemia.

Aims/hypothesis: ALR/Lt, a mouse strain with strong resistance to type 1 diabetes, is closely related to autoimmune type 1 diabetes-prone NOD/Lt mice. ALR pancreatic beta cells are resistant to the beta cell toxin alloxan, combinations of cytotoxic cytokines, and diabetogenic NOD T-cell lines. Reciprocal F1 hybrids between either ALR and NOD or ALR and NON/Lt, showed that alloxan resistance was transmitted to F1 progeny only when ALR was the maternal parent. Here we show that the mitochondrial genome (mtDNA) of ALR mice contributes resistance to diabetes. Methods: When F1 progeny from reciprocal outcrosses between ALR and NOD were backcrossed to NOD, a four-fold lower frequency of spontaneous type 1 diabetes development occurred when ALR contributed the mtDNA. Because of the apparent interaction between nuclear and mtDNA, the mitochondrial genomes were sequenced. Results: An ALR-specific sequence variation in the mt-Nd2 gene producing a leucine to methionine substitution at amino acid residue 276 in the NADH dehydrogenase 2 was discovered. An isoleucine to valine mutation in the mt-Co3 gene encoding COX3 distinguished ALR and NOD from NON and ALS. All four strains were distinguished by variation in a mt-encoded arginyl tRNA polyadenine tract. Shared alleles of mt-Co3 and mt-Tr comparing NOD and ALR allowed for exclusion of these two genes as candidates, implicating the mt-Nd2 variation as a potential ALR-derived type 1 diabetes protective gene. Conclusions/interpretation: The unusual resistance of ALR mice to both ROS-mediated and autoimmune type 1 diabete stresses reflects an interaction between the nuclear and mt genomes. The latter contribution is most likely via a single nucleotide polymorphism in mt-Nd2.

High-affinity RNA ligands were generated against intact 30S ribosomes, S1-depleted 30S ribosomes, and purified ribosomal protein S1. Sequence analysis indicated two classes of ligand: unstructured RNAs containing a Shine-Dalgarno sequence and structured RNAs containing a pseudoknot. The Shine-Dalgarno-containing ligands were generated against S1-depleted 30S ribosomes but, surprisingly, not against intact 30S ribosomes or ribosomal protein S1. In contrast, pseudoknot-containing ligands were generated against intact ribosomes as well as purified S1 protein. The two classes of ligand exhibited specificity for their respective targets, as well as conserved sequence and secondary structure reminiscent of naturally occurring, cis-acting mRNA elements.