Altered Metabolism during the Dark Period in Drosophila Short Sleep Mutants.

Sleep is regulated via circadian mechanisms, but effects of sleep disruption on physiological rhythms, in particular metabolic cycling, remain unclear. To examine this question, we probed diurnal metabolic alterations of two Drosophila short sleep mutants, fumin and sleepless. Samples were collected with high temporal sampling (every 2 h) over 24 h under a 12:12 light:dark cycle, and profiling was done using an ion-switching LCMS/MS method. Fewer metabolites with 24 h oscillations were noted with short sleep (50 and 46 in fumin and sleepless, BH. Q < 0.2 by RAIN analysis) compared to a wild-type control (iso31, 63 with BH. Q < 0.2), and peak phases of the sleep mutants were consolidated into two major phase peaks at mid-day and middle of night. Overall, altered nicotinate/nicotinamide, alanine/aspartate/glutamate, acetylcholine, glyoxylate/dicarboxylate, and TCA cycle metabolism were observed in the short sleep mutants, indicative of increased energetic demand and oxidative stress compared to wild type. Both changes in cycling and discriminant models suggest unique alterations in the dark period indicative of constrained metabolic networks. Thus, we conclude that sleep loss alters metabolic function uniquely throughout the day, and further examination of specific mechanisms is warranted.

Glucose Challenge Uncovers Temporal Fungibility of Metabolic Homeostasis Throughout the Day.

Rhythmicity is a central feature of behavioral and biological processes including metabolism, however, the mechanisms of metabolite cycling are poorly understood. A robust oscillation in a network of key metabolite pathways downstream of glucose is described in humans, then these pathways mechanistically probed through purpose-built 13C6-glucose isotope tracing in Drosophila every 4h. A temporal peak in biosynthesis was noted by broad labelling of pathways downstream of glucose in wild-type flies shortly following lights on. Krebs cycle labelling was generally increased in a hyperactive mutant (fumin) along with glycolysis labelling primarily observed at dawn. Surprisingly, neither underlying feeding rhythms nor the presence of food explains the rhythmicity of glucose processing across genotypes. These results are consistent with clinical data demonstrating detrimental effects of mis-timed energy intake. This approach provides a window into the dynamic range of metabolic processing ability through the day and mechanistic basis for exploring circadian metabolic homeostasis in disease states.

Altered Metabolism During the Dark Period in Drosophila Short Sleep Mutants.

Sleep is an almost universally required state in biology. Disrupted sleep has been associated with adverse health risks including metabolic perturbations. Sleep is in part regulated via circadian mechanisms, however, metabolic dysfunction at different times of day arising from sleep disruption is unclear. We used targeted liquid chromatography-mass spectrometry to probe metabolic alterations using high-resolution temporal sampling of two Drosophila short sleep mutants, fumin and sleepless, across a circadian day. Discriminant analyses revealed overall distinct metabolic profiles for mutants when compared to a wild type dataset. Altered levels of metabolites involved in nicotinate/nicotinamide, alanine, aspartate, and glutamate, glyoxylate and dicarboxylate metabolism, and the TCA cycle were observed in mutants suggesting increased energetic demands. Furthermore, rhythmicity analyses revealed fewer 24 hr rhythmic metabolites in both mutants. Interestingly, mutants displayed two major peaks in phases while wild type displayed phases that were less concerted. In contrast to 24 hr rhythmic metabolites, an increase in the number of 12 hr rhythmic metabolites was observed in fumin while sleepless displayed a decrease. These results support that decreased sleep alters the overall metabolic profile with short sleep mutants displaying altered metabolite levels associated with a number of pathways in addition to altered neurotransmitter levels.

Rhythmic glucose metabolism regulates the redox circadian clockwork in human red blood cells.

Circadian clocks coordinate mammalian behavior and physiology enabling organisms to anticipate 24-hour cycles. Transcription-translation feedback loops are thought to drive these clocks in most of mammalian cells. However, red blood cells (RBCs), which do not contain a nucleus, and cannot perform transcription or translation, nonetheless exhibit circadian redox rhythms. Here we show human RBCs display circadian regulation of glucose metabolism, which is required to sustain daily redox oscillations. We found daily rhythms of metabolite levels and flux through glycolysis and the pentose phosphate pathway (PPP). We show that inhibition of critical enzymes in either pathway abolished 24-hour rhythms in metabolic flux and redox oscillations, and determined that metabolic oscillations are necessary for redox rhythmicity. Furthermore, metabolic flux rhythms also occur in nucleated cells, and persist when the core transcriptional circadian clockwork is absent in Bmal1 knockouts. Thus, we propose that rhythmic glucose metabolism is an integral process in circadian rhythms.

Circadian and Sleep Metabolomics Across Species.

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

Astrocyte HIF-2α supports learning in a passive avoidance paradigm under hypoxic stress.

BACKGROUND: The brain is extensively vascularized, uses20% of the body's oxygen, and is highly sensitive to changes in oxygen. While synaptic plasticity and memory are impaired in healthy individuals by exposure to mild hypoxia, aged individuals appear to be even more sensitive. Aging is associated with progressive failure in pulmonary and cardiovascular systems, exposing the aged to both chronic and superimposed acute hypoxia. The HIF proteins, the "master regulators" of the cellular response to hypoxia, are robustly expressed in neurons and astrocytes. Astrocytes support neurons and synaptic plasticity via complex metabolic and trophic mechanisms. The activity of HIF proteins in the brain is diminished with aging, and the increased exposure to chronic and acute hypoxia with aging combined with diminished HIF activity may impair synaptic plasticity. PURPOSE: Herein, we test the hypothesis that astrocyte HIF supports synaptic plasticity and learning upon hypoxia. MATERIALS AND METHODS: An Astrocyte-specific HIF loss-of-function model was employed, where knock-out of HIF-1α or HIF-2α in GFAP expressing cells was accomplished by cre-mediated recombination. Animals were tested for behavioral (open field and rotarod), learning (passive avoidance paradigm), and electrophysiological (long term potentiation) responses to mild hypoxic challenge. RESULTS: In an astrocyte-specific HIF loss-of-function model followed by mild hypoxia, we identified that the depletion of HIF-2α resulted in an impaired passive avoidance learning performance. This was accompanied by an attenuated response to induction in long-term potentiation (LTP), suggesting that the hippocampal circuitry was perturbed upon hypoxic exposure following HIF-2α loss in astrocytes, and not due to hippocampal cell death. We investigated HIF-regulated trophic and metabolic target genes and found that they were not regulated by HIF-2α, suggesting that these specific targets may not be involved in mediating the phenotypes observed. CONCLUSION: Together, these results point to a role for HIF-2α in the astrocyte's regulatory role in synaptic plasticity and learning under hypoxia and suggest that even mild, acute hypoxic challenges can impair cognitive performance in the aged population who harbor impaired HIF function.

Extraction and Analysis of Pan-metabolome Polar Metabolites by Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS).

Modern triple quadrupole mass spectrometers provide the ability to detect and quantify a large number of metabolites using tandem mass spectrometry (MS/MS). Liquid chromatography (LC) is advantageous, as it does not require derivatization procedures and a large diversity in physiochemical characteristics of analytes can be accommodated through a variety of column chemistries. Recently, the comprehensive optimization of LC-MS metabolomics using design of experiments (COLMeD) approach has been described and used by our group to develop robust LC-MS workflows (Rhoades and Weljie, 2016). The optimized LC-MS/MS method described here has been utilized extensively for metabolomics analysis of polar metabolites. Typically, tissue or biofluid samples are extracted using a modified Bligh-Dyer protocol (Bligh and Dyer, 1959; Tambellini et al., 2013). The protocol described herein describes this workflow using targeted polar metabolite multiple reaction monitoring (MRM) from tissues and biofluids via ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). This workflow has been utilized extensively for chronometabolic analysis (Krishnaiah et al., 2017), with applications generalized to other types of analyses as well (Sengupta et al., 2017; Sivanand et al., 2017).