The Central Clock Neurons Regulate Lipid Storage in Drosophila

A proper balance of lipid breakdown and synthesis is essential for achieving energy homeostasis as alterations in either of these processes can lead to pathological states such as obesity. The regulation of lipid metabolism is quite complex with multiple signals integrated to control overall triglyceride levels in metabolic tissues. Based upon studies demonstrating effects of the circadian clock on metabolism, we sought to determine if the central clock cells in the Drosophila brain contribute to lipid levels in the fat body, the main nutrient storage organ of the fly. Here, we show that altering the function of the Drosophila central clock neurons leads to an increase in fat body triglycerides. We also show that although triglyceride levels are not affected by age, they are increased by expression of the amyloid-beta protein in central clock neurons. The effect on lipid storage seems to be independent of circadian clock output as changes in triglycerides are not always observed in genetic manipulations that result in altered locomotor rhythms. These data demonstrate that the activity of the central clock neurons is necessary for proper lipid storage

Circadian Rhythms of Fetal Liver Transcription Persist in the Absence of Canonical Circadian Clock Gene Expression Rhythms In Vivo

The cellular circadian clock and systemic cues drive rhythmicity in the transcriptome of adult peripheral tissues. However, the oscillating status of the circadian clocks in fetal tissues, and their response to maternal cues, are less clear. Most clock genes do not cycle in fetal livers from mice and rats, although tissue level rhythms rapidly emerge when fetal mouse liver explants are cultured in vitro. Thus, in the fetal mouse liver, the circadian clock does not oscillate at the cellular level (but is induced to oscillate in culture). To gain a comprehensive overview of the clock status in the fetal liver during late gestation, we performed microarray analyses on fetal liver tissues. In the fetal liver we did not observe circadian rhythms of clock gene expression or many other transcripts known to be rhythmically expressed in the adult liver. Nevertheless, JTK_CYCLE analysis identified some transcripts in the fetal liver that were rhythmically expressed, albeit at low amplitudes. Upon data filtering by coefficient of variation, the expression levels for transcripts related to pancreatic exocrine enzymes and zymogen secretion were found to undergo synchronized daily fluctuations at high amplitudes. These results suggest that maternal cues influence the fetal liver, despite the fact that we did not detect circadian rhythms of canonical clock gene expression in the fetal liver. These results raise important questions on the role of the circadian clock, or lack thereof, during ontogeny

REV-ERBα Participates in Circadian SREBP Signaling and Bile Acid Homeostasis

The nuclear receptor REV-ERBα shapes the daily activity profile of Sterol Response Element Binding Protein (SREBP) and thereby participates in the circadian control of cholesterol and bile acid synthesis in the liver

Genome-Wide and Phase-Specific DNA-Binding Rhythms of BMAL1 Control Circadian Output Functions in Mouse Liver

Temporal mapping during a circadian day of binding sites for the BMAL1 transcription factor in mouse liver reveals genome-wide daily rhythms in DNA binding and uncovers output functions that are controlled by the circadian oscillator

Systemic Computation using Graphics Processors

Abstract. Previous work created the systemic computer – a model of computation designed to exploit many natural properties observed in biological systems, including parallelism. The approach has been proven through two existing implementations and many biological models and visualizations. However to date the systemic computer implementations have all been sequential simulations that do not exploit the true potential of the model. In this paper the first parallel implementation of systemic computation is introduced. The GPU Systemic Computation Architecture is the first implementation that enables parallel systemic computation by exploiting multiple cores available in graphics processors. Comparisons with the serial implementation when running a genetic algorithm at different scales show that as the number of systems increases, the parallel architecture is several hundred times faster than the existing implementations, making it feasible to investigate systemic models of more complex biological systems. Keywords: Bio-inspired computation; systemic computation; GPU; parallel architectures; genetic algorithm