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.

PHGDH-mediated endothelial metabolism drives glioblastoma resistance to chimeric antigen receptor T cell immunotherapy.

The efficacy of immunotherapy is limited by the paucity of T cells delivered and infiltrated into the tumors through aberrant tumor vasculature. Here, we report that phosphoglycerate dehydrogenase (PHGDH)-mediated endothelial cell (EC) metabolism fuels the formation of a hypoxic and immune-hostile vascular microenvironment, driving glioblastoma (GBM) resistance to chimeric antigen receptor (CAR)-T cell immunotherapy. Our metabolome and transcriptome analyses of human and mouse GBM tumors identify that PHGDH expression and serine metabolism are preferentially altered in tumor ECs. Tumor microenvironmental cues induce ATF4-mediated PHGDH expression in ECs, triggering a redox-dependent mechanism that regulates endothelial glycolysis and leads to EC overgrowth. Genetic PHGDH ablation in ECs prunes over-sprouting vasculature, abrogates intratumoral hypoxia, and improves T cell infiltration into the tumors. PHGDH inhibition activates anti-tumor T cell immunity and sensitizes GBM to CAR T therapy. Thus, reprogramming endothelial metabolism by targeting PHGDH may offer a unique opportunity to improve T cell-based immunotherapy.

CRY1-CBS binding regulates circadian clock function and metabolism.

Circadian disruption influences metabolic health. Metabolism modulates circadian function. However, the mechanisms coupling circadian rhythms and metabolism remain poorly understood. Here, we report that cystathionine ß-synthase (CBS), a central enzyme in one-carbon metabolism, functionally interacts with the core circadian protein cryptochrome 1 (CRY1). In cells, CBS augments CRY1-mediated repression of the CLOCK/BMAL1 complex and shortens circadian period. Notably, we find that mutant CBS-I278T protein, the most common cause of homocystinuria, does not bind CRY1 or regulate its repressor activity. Transgenic CbsZn/Zn  mice, while maintaining circadian locomotor activity period, exhibit reduced circadian power and increased expression of E-BOX outputs. CBS function is reciprocally influenced by CRY1 binding. CRY1 modulates enzymatic activity of the CBS. Liver extracts from Cry1-/- mice show reduced CBS activity that normalizes after the addition of exogenous wild-type (WT) CRY1. Metabolomic analysis of WT, CbsZn/Zn , Cry1-/- , and Cry2-/- samples highlights the metabolic importance of endogenous CRY1. We observed temporal variation in one-carbon and transsulfuration pathways attributable to CRY1-induced CBS activation. CBS-CRY1 binding provides a post-translational switch to modulate cellular circadian physiology and metabolic control.

Cox regression increases power to detect genotype-phenotype associations in genomic studies using the electronic health record.

BACKGROUND: The growth of DNA biobanks linked to data from electronic health records (EHRs) has enabled the discovery of numerous associations between genomic variants and clinical phenotypes. Nonetheless, although clinical data are generally longitudinal, standard approaches for detecting genotype-phenotype associations in such linked data, notably logistic regression, do not naturally account for variation in the period of follow-up or the time at which an event occurs. Here we explored the advantages of quantifying associations using Cox proportional hazards regression, which can account for the age at which a patient first visited the healthcare system (left truncation) and the age at which a patient either last visited the healthcare system or acquired a particular phenotype (right censoring). RESULTS: In comprehensive simulations, we found that, compared to logistic regression, Cox regression had greater power at equivalent Type I error. We then scanned for genotype-phenotype associations using logistic regression and Cox regression on 50 phenotypes derived from the EHRs of 49,792 genotyped individuals. Consistent with the findings from our simulations, Cox regression had approximately 10% greater relative sensitivity for detecting known associations from the NHGRI-EBI GWAS Catalog. In terms of effect sizes, the hazard ratios estimated by Cox regression were strongly correlated with the odds ratios estimated by logistic regression. CONCLUSIONS: As longitudinal health-related data continue to grow, Cox regression may improve our ability to identify the genetic basis for a wide range of human phenotypes.

Misregulation of Drosophila Myc Disrupts Circadian Behavior and Metabolism.

Drosophila Myc (dMyc) is highly conserved and functions as a transcription factor similar to mammalian Myc. We previously found that oncogenic Myc disrupts the molecular clock in cancer cells. Here, we demonstrate that misregulation of dMyc expression affects Drosophila circadian behavior. dMyc overexpression results in a high percentage of arrhythmic flies, concomitant with increases in the expression of clock genes cyc, tim, cry, and cwo. Conversely, flies with hypomorphic mutations in dMyc exhibit considerable arrhythmia, which can be rescued by loss of dMnt, a suppressor of dMyc activity. Metabolic profiling of fly heads revealed that loss of dMyc and its overexpression alter steady-state metabolite levels and have opposing effects on histidine, the histamine precursor, which is rescued in dMyc mutants by ablation of dMnt and could contribute to effects of dMyc on locomotor behavior. Our results demonstrate a role of dMyc in modulating Drosophila circadian clock, behavior, and metabolism.

Pulling the covers in electronic health records for an association study with self-reported sleep behaviors.

The electronic health record (EHR) contains rich histories of clinical care, but has not traditionally been mined for information related to sleep habits. Here, we performed a retrospective EHR study based on a cohort of 3,652 individuals with self-reported sleep behaviors documented from visits to the sleep clinic. These individuals were obese (mean body mass index 33.6 kg/m2) and had a high prevalence of sleep apnea (60.5%), however we found sleep behaviors largely concordant with prior prospective cohort studies. In our cohort, average wake time was 1 hour later and average sleep duration was 40 minutes longer on weekends than on weekdays (p < 10-12). Sleep duration varied considerably as a function of age and tended to be longer in females and in whites. Additionally, through phenome-wide association analyses, we found an association of long weekend sleep with depression, and an unexpectedly large number of associations of long weekday sleep with mental health and neurological disorders (q < 0.05). We then sought to replicate previously published genetic associations with morning/evening preference on a subset of our cohort with extant genotyping data (n = 555). While those findings did not replicate in our cohort, a polymorphism (rs3754214) in high linkage disequilibrium with a previously published polymorphism near TARS2 was associated with long sleep duration (p < 0.01). Collectively, our results highlight the potential of the EHR for uncovering the correlates of human sleep in real-world populations.

Cyclooxygenase-2, Asymmetric Dimethylarginine, and the Cardiovascular Hazard From Nonsteroidal Anti-Inflammatory Drugs.

BACKGROUND: Large-scale, placebo-controlled trials established that nonsteroidal anti-inflammatory drugs confer a cardiovascular hazard: this has been attributed to depression of cardioprotective products of cyclooxygenase (COX)-2, especially prostacyclin. An alternative mechanism by which nonsteroidal anti-inflammatory drugs might constrain cardioprotection is by enhancing the formation of methylarginines in the kidney that would limit the action of nitric oxide throughout the vasculature. METHODS: Targeted and untargeted metabolomics were used to investigate the effect of COX-2 deletion or inhibition in mice and in osteoarthritis patients exposed to nonsteroidal anti-inflammatory drugs on the l-arginine/nitric oxide pathway. RESULTS: Analysis of the plasma and renal metabolome was performed in postnatal tamoxifen-inducible Cox-2 knockout mice, which exhibit normal renal function and blood pressure. This revealed no changes in arginine and methylarginines compared with their wild-type controls. Moreover, the expression of genes in the l-arginine/nitric oxide pathway was not altered in the renal medulla or cortex of tamoxifen inducible Cox-2 knockout mice. Therapeutic concentrations of the selective COX-2 inhibitors, rofecoxib, celecoxib, and parecoxib, none of which altered basal blood pressure or renal function as reflected by plasma creatinine, failed to elevate plasma arginine and methylarginines in mice. Finally, plasma arginine or methylarginines were not altered in osteoarthritis patients with confirmed exposure to nonsteroidal anti-inflammatory drugs that inhibit COX-1 and COX-2. By contrast, plasma asymmetrical dimethylarginine was increased in mice infused with angiotensin II sufficient to elevate blood pressure and impair renal function. Four weeks later, blood pressure, plasma creatinine, and asymmetrical dimethylarginine were restored to normal levels. The increase in asymmetrical dimethylarginine in response to infusion with angiotensin II in celecoxib-treated mice was also related to transient impairment of renal function. CONCLUSIONS: Plasma methylarginines are not altered by COX-2 deletion or inhibition but rather are elevated coincident with renal compromise.

Circadian- and Light-driven Metabolic Rhythms in Drosophila melanogaster.

Complex interactions of environmental cues and transcriptional clocks drive rhythmicity in organismal physiology. Light directly affects the circadian clock; however, little is known about its relative role in controlling metabolic variations in vivo. Here we used high time-resolution sampling in Drosophila at every 2 h to measure metabolite outputs using a liquid-chromatography tandem mass spectrometry (LC-MS/MS) approach. Over 14% of detected metabolites oscillated with circadian periodicity under light-dark (LD) cycles. Many metabolites peaked shortly after lights-on, suggesting responsiveness to feeding and/or activity rather than the preactivity anticipation, as observed in previous transcriptomics analyses. Roughly 9% of measured metabolites uniquely oscillated under constant darkness (DD), suggesting that metabolite rhythms are associated with the transcriptional clock machinery. Strikingly, metabolome differences between LD and constant darkness were observed only during the light phase, highlighting the importance of photic input. Clock mutant flies exhibited strong 12-h ultradian rhythms, including 4 carbohydrate species with circadian periods in wild-type flies, but lacked 24-h circadian metabolic oscillations. A meta-analysis of these results with previous circadian metabolomics experiments uncovered the possibility of conserved rhythms in amino acids, keto-acids, and sugars across flies, mice, and humans and provides a basis for exploring the chrono-metabolic connection with powerful genetic tools in Drosophila.

A Pilot Characterization of the Human Chronobiome.

Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the "noise" attributable to the behavioral differences of free-living human volunteers. The majority (62%) of sensor readouts showed time-specific variability including the expected variation in blood pressure, heart rate, and cortisol. While variance in the multi-omics is dominated by inter-individual differences, temporal patterns are evident in the metabolome (5.4% in plasma, 5.6% in saliva) and in several genera of the oral microbiome. This demonstrates, despite a small sample size and limited sampling, the feasibility of characterizing at scale the human chronobiome "in the wild". Such reference data at scale are a prerequisite to detect and mechanistically interpret discordant data derived from patients with temporal patterns of disease expression, to develop time-specific therapeutic strategies and to refine existing treatments.

Sleep restriction induced energy, methylation and lipogenesis metabolic switches in rat liver.

Sleep curtailment is ubiquitous in modern day society. Sleep debt is associated with maladaptive physiological changes that can lead to cardiometabolic and neuropsychiatric pathologies. Recent literature has shown the effects of sleep restriction (SR) on systemic metabolic profiles in biofluids, implying that tissue-specific metabolomes are impacted by SR. To test this hypothesis, we assessed hepatic metabolic profiles of rats after 5days of SR using UPLC-MS based metabolomics analysis and gene expression analysis. Our data suggests distinctive effects of SR on the liver metabolic profile of rats compared to forced-activity control animals. We observed specific impacts of SR on NAD metabolism through NAD accumulation and upregulation of Nampt, the rate determining step of NAD salvage. Additional multi-omic changes were observed in methionine metabolism, with an elevated SAM:SAH ratio under SR. This effect on one carbon metabolism is indicative of increased methylation potential. Changes in TCA cycle intermediates and ATP-citrate lyase (Acly) gene expression were observed that may be related to altered circulatory lipid profiles previously reported documenting the chrono-metabolic connection. Taken together with previous investigations, these observations are consistent with a model of decreased TCA activity with concomitant increase in lipogenesis induced by SR. These tissue-specific mechanistic insights into metabolic effects of SR provide a springboard to future metabolic intervention studies.

Clock Regulation of Metabolites Reveals Coupling between Transcription and Metabolism.

The intricate connection between the circadian clock and metabolism remains poorly understood. We used high temporal resolution metabolite profiling to explore clock regulation of mouse liver and cell-autonomous metabolism. In liver, ∼50% of metabolites were circadian, with enrichment of nucleotide, amino acid, and methylation pathways. In U2 OS cells, 28% were circadian, including amino acids and NAD biosynthesis metabolites. Eighteen metabolites oscillated in both systems and a subset of these in primary hepatocytes. These 18 metabolites were enriched in methylation and amino acid pathways. To assess clock dependence of these rhythms, we used genetic perturbation. BMAL1 knockdown diminished metabolite rhythms, while CRY1 or CRY2 perturbation generally shortened or lengthened rhythms, respectively. Surprisingly, CRY1 knockdown induced 8 hr rhythms in amino acid, methylation, and vitamin metabolites, decoupling metabolite from transcriptional rhythms, with potential impact on nutrient sensing in vivo. These results provide the first comprehensive views of circadian liver and cell-autonomous metabolism.

Time is ripe: maturation of metabolomics in chronobiology.

Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies.

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD).

INTRODUCTION: Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. OBJECTIVE: Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). METHODS: We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. RESULTS: LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. CONCLUSIONS: The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.