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

Differential Impact In Vivo of Pf4-ΔCre-Mediated and Gp1ba-ΔCre-Mediated Depletion of Cyclooxygenase-1 in Platelets in Mice

BACKGROUND

Low-dose aspirin is widely used for the secondary prevention of cardiovascular disease. The beneficial effects of low-dose aspirin are attributable to its inhibition of platelet Cox (cyclooxygenase)-1-derived thromboxane A2. Until recently, the use of the Pf4 (platelet factor 4) Cre has been the only genetic approach to generating megakaryocyte/platelet ablation of Cox-1 in mice. However, Pf4-ΔCre displays ectopic expression outside the megakaryocyte/platelet lineage, especially during inflammation. The use of the Gp1ba (glycoprotein 1bα) Cre promises a more specific, targeted approach.

METHODS

To evaluate the role of Cox-1 in platelets, we crossed Pf4-ΔCre or Gp1ba-ΔCre mice with Cox-1flox/flox mice to generate platelet Cox-1-/- mice on normolipidemic and hyperlipidemic (Ldlr-/-; low-density lipoprotein receptor) backgrounds.

RESULTS

Ex vivo platelet aggregation induced by arachidonic acid or adenosine diphosphate in platelet-rich plasma was inhibited to a similar extent in Pf4-ΔCre Cox-1-/-/Ldlr-/- and Gp1ba-ΔCre Cox-1-/-/Ldlr-/- mice. In a mouse model of tail injury, Pf4-ΔCre-mediated and Gp1ba-ΔCre-mediated deletions of Cox-1 were similarly efficient in suppressing platelet prostanoid biosynthesis. Experimental thrombogenesis and attendant blood loss were similar in both models. However, the impact on atherogenesis was divergent, being accelerated in the Pf4-ΔCre mice while restrained in the Gp1ba-ΔCres. In the former, accelerated atherogenesis was associated with greater suppression of PGI2 biosynthesis, a reduction in the lipopolysaccharide-evoked capacity to produce PGE2 (prostaglandin E) and PGD2 (prostanglandin D), activation of the inflammasome, elevated plasma levels of IL-1β (interleukin), reduced plasma levels of HDL-C (high-density lipoprotein receptor-cholesterol), and a reduction in the capacity for reverse cholesterol transport. By contrast, in the latter, plasma HDL-C and α-tocopherol were elevated, and MIP-1α (macrophage inflammatory protein-1α) and MCP-1 (monocyte chemoattractant protein 1) were reduced.

CONCLUSIONS

Both approaches to Cox-1 deletion similarly restrain thrombogenesis, but a differential impact on Cox-1-dependent prostanoid formation by the vasculature may contribute to an inflammatory phenotype and accelerated atherogenesis in Pf4-ΔCre mice.

Antifungal mechanisms investigation of lactic acid bacteria against Aspergillus flavus: through combining microbial metabolomics and co-culture system

AIMS

To develop antifungal lactic acid bacteria (LAB) and investigate their antifungal mechanisms against Aspergillus flavus in aflatoxin (AF) production.

METHODS AND RESULTS

We isolated 179 LABs from cereal-based fermentation starters and investigated their antifungal mechanism against A. flavus through liquid chromatography-mass spectrometry and co-culture analysis techniques. Of the 179 isolates, antifungal activity was identified in Pediococcus pentosaceus, Lactobacillus crustorum, and Weissella paramesenteroides. These LABs reduced AF concentration by (i) inhibiting mycelial growth, (ii) binding AF to the cell wall, and (iii) producing antifungal compounds. Species-specific activities were also observed, with P. pentosaceus inhibiting AF production and W. paramesenteroides showing AF B1 binding activity. In addition, crucial extracellular metabolites for selecting antifungal LAB were involved in the 2',3'-cAMP-adenosine and nucleoside pathways.

CONCLUSIONS

This study demonstrates that P. pentosaceus, L. crustorum, and W. paramesenteroides are key LAB strains with distinct antifungal mechanisms against A. flavus, suggesting their potential as biological agents to reduce AF in food materials.

Solvent Composition Can Have a Measurable Influence on the Ion Mobility-Derived Collision Cross Section of Small Molecules

Ion mobility (IM) is an important analytical technique for increasing identification coverage of metabolites in untargeted studies, especially when integrated into traditional liquid chromatography-mass spectrometry workflows. While there has been extensive work surrounding best practices to obtain and standardize collision cross section (CCS) measurements necessary for comparing across different IM techniques and laboratories, there has been little investigation into experimental factors beyond the mobility separation region that could potentially influence CCS measurements. The first-principles derived CCS of 15 chemical standards were evaluated across 27 aqueous:organic solvent compositions using a high-precision drift tube instrument. A small but measurable dependency of the CCS on the solvent composition was observed, with the larger analytes from this study (m/z > 400) exhibiting a characteristic increase in CCS at the intermediate (40-60%) solvent compositions. Parallels to the behavior of solvent viscosity and protonation site tautomers (protomers) were noted, although the origin of these solvent-dependent CCS trends is as yet unclear. Taken together, these findings document a solvent dependency on CCS, which, while minor (<0.5%), identifies an important need for reporting the solvent system when utilizing CCS in comparative ion mobility studies.

Sleep deprivation and aging are metabolically linked across tissues

STUDY OBJECTIVES

Insufficient sleep is a concerning hallmark of modern society because sleep deprivation (SD) is a risk factor for neurodegenerative and cardiometabolic disorders. SD imparts an aging-like effect on learning and memory, although little is known about possible common molecular underpinnings of SD and aging. Here, we examine this question by profiling metabolic features across different tissues after acute SD in young adult and aged mice.

METHODS

Young adult and aged mice were subjected to acute SD for 5 hours. Blood plasma, hippocampus, and liver samples were subjected to UPLC-MS/MS-based metabolic profiling.

RESULTS

SD preferentially impacts peripheral plasma and liver profiles (e.g. ketone body metabolism) whereas the hippocampus is more impacted by aging. We further demonstrate that aged animals exhibit SD-like metabolic features at baseline. Hepatic alterations include parallel changes in nicotinamide metabolism between aging and SD in young animals. Overall, metabolism in young adult animals is more impacted by SD, which in turn induces aging-like features. A set of nine metabolites was classified (79% correct) based on age and sleep status across all four groups.

CONCLUSIONS

Our metabolic observations demonstrate striking parallels to previous observations in studies of learning and memory and define a molecular metabolic signature of sleep loss and aging.

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.

Critical evaluation of MS acquisition conditions and identification process in LC-Q-Orbitrap-MS for non-targeted analysis: pesticide residues as case of study

In routine measurements, the length of analysis time and the number of samples analysed during a given time unit are crucial. Additionally, the analytical method used has to provide reliable results and be able to identify and quantify any compound present in the matrix. High-resolution equipment, including Orbitrap analysers, is commonly used for non-targeted determinations. However, researchers still rely on trial and error to achieve the best acquisition conditions on the mass spectrometer, which is a tedious and time-consuming process that can lead to errors. Moreover, tentative compound identification, particularly when using a non-targeted approach, heavily depends on commercial databases. All of these issues can ultimately result in incomplete identification of compounds in the study matrix. In this framework, the study presented here has a dual objective: to use the experimental design tool to optimise critical parameters in mass spectrometry using LC-Q-Orbitrap-MS equipment when working in a non-targeted approach and to compare the mzCloud™ and ChemSpider™ commercial databases included in Compound Discoverer software with TraceFinder home-made databases generated to evaluate the ability to identify compounds. The study's noteworthy findings reveal that employing an experimental design has facilitated rapid optimisation of the mass spectrometer's multiplexing and loop parameters. Furthermore, the study highlights that the lack of harmonisation in commercial databases poses a disadvantage in the identification of compounds, leading to superior results when using home-made databases. In the latter databases, around 80% of the compounds were identified, which is approximately twice the number identified in commercial databases (around 40% in the best case with ChemSpider™).

MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis

The molecular circadian clock, which controls rhythmic 24-hour oscillation of genes, proteins, and metabolites in healthy tissues, is disrupted across many human cancers. Deregulated expression of the MYC oncoprotein has been shown to alter expression of molecular clock genes, leading to a disruption of molecular clock oscillation across cancer types. It remains unclear what benefit cancer cells gain from suppressing clock oscillation, and how this loss of molecular clock oscillation impacts global gene expression and metabolism in cancer. We hypothesized that MYC or its paralog N-MYC (collectively termed MYC herein) suppress oscillation of gene expression and metabolism to upregulate pathways involved in biosynthesis in a static, non-oscillatory fashion. To test this, cells from distinct cancer types with inducible MYC were examined, using time-series RNA-sequencing and metabolomics, to determine the extent to which MYC activation disrupts global oscillation of genes, gene expression pathways, and metabolites. We focused our analyses on genes, pathways, and metabolites that changed in common across multiple cancer cell line models. We report here that MYC disrupted over 85% of oscillating genes, while instead promoting enhanced ribosomal and mitochondrial biogenesis and suppressed cell attachment pathways. Notably, when MYC is activated, biosynthetic programs that were formerly circadian flipped to being upregulated in an oscillation-free manner. Further, activation of MYC ablates the oscillation of nutrient transporter proteins while greatly upregulating transporter expression, cell surface localization, and intracellular amino acid pools. Finally, we report that MYC disrupts metabolite oscillations and the temporal segregation of amino acid metabolism from nucleotide metabolism. Our results demonstrate that MYC disruption of the molecular circadian clock releases metabolic and biosynthetic processes from circadian control, which may provide a distinct advantage to cancer cells.

MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis

The molecular circadian clock, which controls rhythmic 24-hour oscillation of genes, proteins, and metabolites in healthy tissues, is disrupted across many human cancers. Deregulated expression of the MYC oncoprotein has been shown to alter expression of molecular clock genes, leading to a disruption of molecular clock oscillation across cancer types. It remains unclear what benefit cancer cells gain from suppressing clock oscillation, and how this loss of molecular clock oscillation impacts global gene expression and metabolism in cancer. We hypothesized that MYC or its paralog N-MYC (collectively termed MYC herein) suppress oscillation of gene expression and metabolism to upregulate pathways involved in biosynthesis in a static, non-oscillatory fashion. To test this, cells from distinct cancer types with inducible MYC were examined, using time-series RNA-sequencing and metabolomics, to determine the extent to which MYC activation disrupts global oscillation of genes, gene expression pathways, and metabolites. We focused our analyses on genes, pathways, and metabolites that changed in common across multiple cancer cell line models. We report here that MYC disrupted over 85% of oscillating genes, while instead promoting enhanced ribosomal and mitochondrial biogenesis and suppressed cell attachment pathways. Notably, when MYC is activated, biosynthetic programs that were formerly circadian flipped to being upregulated in an oscillation-free manner. Further, activation of MYC ablates the oscillation of nutrient transporter proteins while greatly upregulating transporter expression, cell surface localization, and intracellular amino acid pools. Finally, we report that MYC disrupts metabolite oscillations and the temporal segregation of amino acid metabolism from nucleotide metabolism. Our results demonstrate that MYC disruption of the molecular circadian clock releases metabolic and biosynthetic processes from circadian control, which may provide a distinct advantage to cancer cells.

Chronic sleep loss sensitizes Drosophila melanogaster to nitrogen stress

Chronic sleep loss profoundly impacts metabolic health and shortens lifespan, but studies of the mechanisms involved have focused largely on acute sleep deprivation.1,2 To identify metabolic consequences of chronically reduced sleep, we conducted unbiased metabolomics on heads of three adult Drosophila short-sleeping mutants with very different mechanisms of sleep loss: fumin (fmn), redeye (rye), and sleepless (sss).3,4,5,6,7 Common features included elevated ornithine and polyamines, with lipid, acyl-carnitine, and TCA cycle changes suggesting mitochondrial dysfunction. Studies of excretion demonstrate inefficient nitrogen elimination in adult sleep mutants, likely contributing to their polyamine accumulation. Increasing levels of polyamines, particularly putrescine, promote sleep in control flies but poison sleep mutants. This parallels the broadly enhanced toxicity of high dietary nitrogen load from protein in chronically sleep-restricted Drosophila, including both sleep mutants and flies with hyper-activated wake-promoting neurons. Together, our results implicate nitrogen stress as a novel mechanism linking chronic sleep loss to adverse health outcomes-and perhaps for linking food and sleep homeostasis at the cellular level in healthy organisms.

Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning

The combination of retention time (RT), accurate mass and tandem mass spectra can improve the structural annotation in untargeted metabolomics. However, the incorporation of RT for metabolite identification has received less attention because of the limitation of available RT data, especially for hydrophilic interaction liquid chromatography (HILIC). Here, the Graph Neural Network-based Transfer Learning (GNN-TL) is proposed to train a model for HILIC RTs prediction. The graph neural network was pre-trained using an in silico HILIC RT dataset (pseudo-labeling dataset) with ∼306 K molecules. Then, the weights of dense layers in the pre-trained GNN (pre-GNN) model were fine-tuned by transfer learning using a small number of experimental HILIC RTs from the target chromatographic system. The GNN-TL outperformed the methods in Retip, including the Random Forest (RF), Bayesian-regularized neural network (BRNN), XGBoost, light gradient-boosting machine (LightGBM), and Keras. It achieved the lowest mean absolute error (MAE) of 38.6 s on the test set and 33.4 s on an additional test set. It has the best ability to generalize with a small performance difference between training, test, and additional test sets. Furthermore, the predicted RTs can filter out nearly 60% false positive candidates on average, which is valuable for the identification of compounds complementary to mass spectrometry.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Treatment of Insomnia with Zaleplon in HIV+ Significantly Improves Sleep and Depression

More than 50% of individuals who are HIV positive report insomnia, which can reduce HIV treatment adherence, impair quality of life, and contribute to metabolic dysfunction. Major depressive disorder is also highly comorbid in this population, leading to further impairment. There is evidence that treating insomnia may improve not only sleep, but depression and metabolic function, as well. The present study aimed to examine the effects of pharmacotherapeutic treatment of insomnia on sleep, depression, and metabolic functioning in individuals with HIV. 20 individuals with asymptomatic seropositive HIV and comorbid insomnia and depression were administered zaleplon for 6 weeks. Insomnia severity was assessed using the Insomnia Severity Index and Epworth Sleepiness Scale, and depression severity was assessed using the Quick Inventory of Depression, both prior to treatment and 6 weeks post treatment. Metabolomic changes were assessed using a comprehensive platform measuring ~2000 lipid features and polar metabolites. Linear mixed effects models demonstrated that 6 weeks of treatment with zaleplon significantly improved symptoms of both insomnia and depression. Metabolomic analyses also demonstrated that changes in insomnia severity were associated with significant changes in key branched chain amino acid metabolites. Our results show that improvement in insomnia is associated with reduced depressive symptoms and beneficial metabolomic changes. Additionally, changes in key branched chain amino acid metabolites following treatment may serve as useful biomarkers of treatment response.

Design of experiments for development and optimization of a liquid chromatography coupled to tandem mass spectrometry bioanalytical assay

Design of experiments (DoE) is a valuable tool for the optimization of quantitative bioanalytical methods utilizing liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Liquid chromatography mass spectrometry (LC-MS) is composed of several processes, including, liquid introduction and analyte ionization. The goal is to transfer analytes from atmospheric pressure to vacuum and maintain conditions that are compatible for both LC and MS. These processes involve many experimental factors which need to be simultaneously optimized to obtain maximum sensitivity and resolution at minimum retention time. In this tutorial, the basic concepts of DoE will be explained with focus on practical use of DoE. Three case studies optimized with DoE for liquid chromatography tandem mass spectrometry (LC-MS/MS) quantitative assays will then be presented.

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.

Optimization of metabolite extraction and analytical methods from shrimp intestine for metabolomics profile analysis using LC-HRMS/MS

INTRODUCTION

Intestinal microbiota and metabolites play important roles for further improvement of animal production. Metabolomics of shrimp intestine to understand roles and their relationship to the host is hampered by the lack of metabolome profiling method.

OBJECTIVES

This study aims to develop extraction and analytical methods to allow accurate metabolic analysis in shrimp intestine.

METHODS

Conditions for extraction and LC-HRMS/MS analysis were optimized.

RESULTS

Extraction with ethyl acetate:acetone (15:2 v/v) acidified with 0.5% acetic acid, elution with acetonitrile:water acidified with 0.01% acetic acid for 25 min, and mass fragmentation at 15% HCD were the optimal conditions, yielding the highest signal intensity and numbers of putative metabolites.

CONCLUSION

Our method enabled in-depth study for shrimp-microbial interaction at metabolite level.

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.

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.

Targeting glutamine metabolism slows soft tissue sarcoma growth

Tumour cells frequently utilize glutamine to meet bioenergetic and biosynthetic demands of rapid cell growth. However, glutamine dependence can be highly variable between in vitro and in vivo settings, based on surrounding microenvironments and complex adaptive responses to glutamine deprivation. Soft tissue sarcomas (STSs) are mesenchymal tumours where cytotoxic chemotherapy remains the primary approach for metastatic or unresectable disease. Therefore, it is critical to identify alternate therapies to improve patient outcomes. Using autochthonous STS murine models and unbiased metabolomics, we demonstrate that glutamine metabolism supports sarcomagenesis. STS subtypes expressing elevated glutaminase (GLS) levels are highly sensitive to glutamine starvation. In contrast to previous studies, treatment of autochthonous tumour-bearing animals with Telaglenastat (CB-839), an orally bioavailable GLS inhibitor, successfully inhibits undifferentiated pleomorphic sarcoma (UPS) tumour growth. We reveal glutamine metabolism as critical for sarcomagenesis, with CB-839 exhibiting potent therapeutic potential.

A large-scale analysis of targeted metabolomics data from heterogeneous biological samples provides insights into metabolite dynamics

INTRODUCTION

We previously developed a tandem mass spectrometry-based label-free targeted metabolomics analysis framework coupled to two distinct chromatographic methods, reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC), with dynamic multiple reaction monitoring (dMRM) for simultaneous detection of over 200 metabolites to study core metabolic pathways.

OBJECTIVES

We aim to analyze a large-scale heterogeneous data compendium generated from our LC-MS/MS platform with both RPLC and HILIC methods to systematically assess measurement quality in biological replicate groups and to investigate metabolite abundance changes and patterns across different biological conditions.

METHODS

Our metabolomics framework was applied in a wide range of experimental systems including cancer cell lines, tumors, extracellular media, primary cells, immune cells, organoids, organs (e.g. pancreata), tissues, and sera from human and mice. We also developed computational and statistical analysis pipelines, which include hierarchical clustering, replicate-group CV analysis, correlation analysis, and case-control paired analysis.

RESULTS

We generated a compendium of 42 heterogeneous deidentified datasets with 635 samples using both RPLC and HILIC methods. There exist metabolite signatures that correspond to various phenotypes of the heterogeneous datasets, involved in several metabolic pathways. The RPLC method shows overall better reproducibility than the HILIC method for most metabolites including polar amino acids. Correlation analysis reveals high confidence metabolites irrespective of experimental systems such as methionine, phenylalanine, and taurine. We also identify homocystine, reduced glutathione, and phosphoenolpyruvic acid as highly dynamic metabolites across all case-control paired samples.

CONCLUSIONS

Our study is expected to serve as a resource and a reference point for a systematic analysis of label-free LC-MS/MS targeted metabolomics data in both RPLC and HILIC methods with dMRM.

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.

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).

Nuclear Acetyl-CoA Production by ACLY Promotes Homologous Recombination

While maintaining the integrity of the genome and sustaining bioenergetics are both fundamental functions of the cell, potential crosstalk between metabolic and DNA repair pathways is poorly understood. Since histone acetylation plays important roles in DNA repair and is sensitive to the availability of acetyl coenzyme A (acetyl-CoA), we investigated a role for metabolic regulation of histone acetylation during the DNA damage response. In this study, we report that nuclear ATP-citrate lyase (ACLY) is phosphorylated at S455 downstream of ataxia telangiectasia mutated (ATM) and AKT following DNA damage. ACLY facilitates histone acetylation at double-strand break (DSB) sites, impairing 53BP1 localization and enabling BRCA1 recruitment and DNA repair by homologous recombination. ACLY phosphorylation and nuclear localization are necessary for its role in promoting BRCA1 recruitment. Upon PARP inhibition, ACLY silencing promotes genomic instability and cell death. Thus, the spatial and temporal control of acetyl-CoA production by ACLY participates in the mechanism of DNA repair pathway choice.

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.