Sir2 and insulin/IGF-1 are the major pathways that impinge upon aging in lower organisms. In Caenorhabditis elegans a possible genetic link between Sir2 and the insulin/IGF-1 pathway has been reported. Here we investigate such a link in mammals. We show that Sirt1 positively regulates insulin secretion in pancreatic β cells. Sirt1 represses the uncoupling protein (UCP) gene UCP2 by binding directly to the UCP2 promoter. In β cell lines in which Sirt1 is reduced by SiRNA, UCP2 levels are elevated and insulin secretion is blunted. The up-regulation of UCP2 is associated with a failure of cells to increase ATP levels after glucose stimulation. Knockdown of UCP2 restores the ability to secrete insulin in cells with reduced Sirt1, showing that UCP2 causes the defect in glucose-stimulated insulin secretion. Food deprivation induces UCP2 in mouse pancreas, which may occur via a reduction in NAD (a derivative of niacin) levels in the pancreas and down-regulation of Sirt1. Sirt1 knockout mice display constitutively high UCP2 expression. Our findings show that Sirt1 regulates UCP2 in β cells to affect insulin secretion.

SummaryWe generated mice that overexpress the sirtuin, SIRT1. Transgenic mice have been generated by knocking in SIRT1 cDNA into the β β β β -actin locus. Mice that are hemizygous for this transgene express normal levels of β β β β -actin and higher levels of SIRT1 protein in several tissues. Transgenic mice display some phenotypes similar to mice on a calorierestricted diet: they are leaner than littermate controls; are more metabolically active; display reductions in blood cholesterol, adipokines, insulin and fasted glucose; and are more glucose tolerant. Furthermore, transgenic mice perform better on a rotarod challenge and also show a delay in reproduction. Our findings suggest that increased expression of SIRT1 in mice elicits beneficial phenotypes that may be relevant to human health and longevity.

Transposon-directed insertion site sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries, and therefore, it remains unclear whether the two methodologies are comparable. To address this, a high-density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false-positive identification of essential genes, statistical data analysis included corrections for both gene length and genome length. Through this analysis, new essential genes and genes previously incorrectly designated essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects, and fine-resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis data sets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.

Understanding gene regulation and its adaptive significance requires not only a detailed knowledge of individual molecular interactions that give rise to changes in gene expression but also an overview of complete genetic networks and the ways in which components within them interact. Increasingly, such studies are being done using luminescent or fluorescent reporter proteins that enable monitoring of gene expression dynamics in real time, particularly during changes in expression. We show here that such an approach is valid for dissecting the responses of the AR2 or GAD network of Escherichia coli K-12 to changes in pH, which is one of the most complex networks known in E. coli. In addition to confirming several regulatory interactions that have been revealed by previous studies, this approach has identified new components in this system that lead to complex dynamics of gene expression following a drop in pH, including an auto-regulatory loop involving the YdeO activator protein and novel roles for the PhoP protein.