Metabolic transitions between hunger and satiety

Studies over the last decade have highlighted the importance of metabolite levels in directing cellular physiology in eukaryotic organisms1,7,8,9,10,11, including in Drosophila12, but how metabolites influence behavior is unclear. To begin investigating this question we set out to identify the metabolic changes that occur during the transition between hunger and satiety in Drosophila melanogaster fruit flies. While many studies have looked at the feeding behaviors of flies fasted for longer (24–48 h) or shorter (0–5 h) times as a proxy for hunger and satiety, we designed a feeding paradigm to specifically capture the transition between these two internal states. To do this, we fasted male flies for 24 h so that they missed their evening and morning meals13,14, then fed them a meal of either agar (fasted) or 400 mM D-glucose agar (refed) for 1 h on the next day (Supplementary Fig. 1a for a schematic of the manipulation). To make sure that a single meal of 400 mM D-glucose was sufficient to switch the behavioral state of flies from hungry to sated, we measured the feeding behaviors of fasted and refed flies using the Fly-to-Liquid-Food Interaction counter (FLIC). The FLIC records the real-time feeding interactions of the fly proboscis with the food five times per second13. While the majority of fasted flies (light green, > 90%) ate on the FLIC, only ~60% of refed flies interacted with the food (Fig. 1a). This was consistent with changes in their motivation to forage for food (Supplementary Fig. 1b, refer to control diet, CD). Over the 1-h period, fasted flies had over three times more feeding interactions than refed flies (Fig. 1b). The number of feeding events, defined as the continuous succession of five or more feeding interactions, was also higher compared to that of refed flies (Fig. 1c). Accordingly, the duration (sec) of each feeding event was longer in fasted flies (Fig. 1d); however, there was no difference in the interval between feeding events (min) and the time it took flies to initiate the first meal on the FLIC (Fig. 1e–f). Thus, our feeding paradigm alters the internal state of flies from hungry to sated in 1 h.

Fig. 1 The feeding behaviors of fasted and refed flies. The feeding behavior of 24 h-fasted (light green, circles) and previously refed (darker green, squares) flies during ad-lib access to 5% sucrose on the FLIC for 1 h (See Supplementary Fig. 1 for a schematic). Individual data points are plotted in all cases. For panels b, c, which were analyzed using a Bayesian model (see Methods for details), bars show the average fitted value and the extent of a 95% credible interval; three asterisks indicate that the posterior probability from Bayesian analysis of a difference in the observed direction is greater than 0.999. For panels d–f plotted bars show a bootstrap-based median and extent of a 95% confidence interval; ***p < 0.001 using a stratified bootstrap. Fasted n = 48, refed n = 38 biologically independent animals. Source data are provided as a Source Data file. See Methods for a detailed description of the behavioral quantification and analysis. a The percentage of fasted and refed flies that interacted with food on the FLIC (green shades), compared to those that did not eat (gray shades). b–f The feeding behavior of flies during the 1-h ad-lib access to 5% sucrose quantified as b the total number of feeding interactions; c the number of feeding events (defined as five of more consecutive feeding interactions above threshold); d the mean duration (sec) among feeding events; e the mean time between 2 or more feeding events (min); f the latency to interact with food (min), calculated as the first feeding interaction initiated on the FLIC. For panels d–f, replicates with no feeding events were excluded (for panels b, c the no-interaction events are explicitly accounted for in our zero-inflated negative binomial model). Source data are provided as a Source Data file Full size image

Previous work has broadly shown that the energy state of fasted flies is different compared to non-fasted flies15. Fasted flies have lower glycogen levels and hemolymph glycemia compared to non-fasted flies16, and circulating glucose levels increase rapidly with refeeding17,18, even if triglycerides do not change (Supplementary Fig. 1c, refer to CD). To identify the metabolites that change during the transition between hunger and satiety, we collected the heads and bodies of fasted and refed flies and performed Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS) across four different platforms. To ensure that metabolism was rapidly quenched during collection and to maximize the number of metabolites measured12, we chose heads and bodies instead of individual tissues. Together, we measured 391 metabolites across 12 conditions (~60 samples, Supplementary Data 1). The median Relative Standard Deviation (RSD) was 3% and 8% for internal standards and biochemicals, respectively, while metabolites in each sample condition have a median value of 30% (Supplementary Data 1). To further assess the technical variation, we performed a Principal Component Analysis (PCA) on all of the data, including samples that were obtained by pooling both the head and bodies (Supplementary Fig. 2). Notably, the pooled samples clustered into a group that was intermediate between the heads and body samples, with a smaller intra-group spread than experimental groups.

Flyscape: a tool to visualize D. melanogaster omics data

As with most omics studies, the analysis of metabolomics data requires computational tools to interpret experimentally determined changes and place them into biological context. A common approach to achieving this involves mapping metabolites onto individual metabolic pathways19,20. However, since one metabolite can be incorporated into several pathways, it can be difficult to understand the impact of changes across many pathways. Though useful, this approach can lead to over-simplification. Our previously published tool Metscape21 took a different approach. Metscape uses pathway information to build metabolic networks, thus allowing a more comprehensive view of the data. However, Metscape is human-centric and to the best of our knowledge none of the other existing tools support the analyses of Drosophila melanogaster metabolism. To overcome this limitation, we developed the user-friendly, open source tool Flyscape. Based on the Metscape frame work, Flyscape can simultaneously visualize D. melanogaster metabolomic and transcriptomic data (Supplementary Fig. 3a). Flyscape is a plug-in for the network analysis and visualization tool Cytoscape22. Flyscape uses the publicly accessible BioCyc23 D. melanogaster metabolic pathway database with gene annotations collected from Flybase24. The Flyscape database contains 4856 metabolites, 2326 enzymes, 15,577 genes, and 2827 reactions. Flyscape can generate four types of network graphs with varying complexity: compound networks where compounds are represented as nodes and reactions are represented as edges (Supplementary Fig. 3b), compound-reaction (Supplementary Fig. 3c), compound-gene (Supplementary Fig. 3d), and compound-reaction-enzyme-gene networks (Supplementary Fig. 3e). In the last three types of networks the respective entities are represented as nodes. Notably, in all types of networks each node is unique and nodes from different pathways can be connected. Further, the networks can be refined by creating subnetworks based on pathways or compounds of interest. This feature allows visualization of changes across different pathways and conditions in a simple, intuitive way. In addition, Flyscape integrates metabolomics data with other types of omics data to build a network of the physiological landscape of the tissue or cell under different conditions.

Bodies and heads show unique metabolic shifts

We analyzed the metabolic profiles of the bodies and heads of refed and fasted flies. PCA showed that the variance between these two datasets was largely due to the feeding state (Supplementary Fig. 4a, b). In the bodies, 61 metabolites changed in abundance between refed and fasted flies (Fig. 2a). Out of these 31 metabolites were increased and 30 metabolites decreased (Welch’s t-test, FDR < 0.1) in refed flies. Compounds higher in refed flies (Fig. 2a) reflect an increase in glucose availability, catabolism (acetyl-CoA, malate, fumarate, lactate), utilization for post-translational modifications (UDP-N-acetylglucosamine, N6-carboxymethyllysine), and storage into glycogen (maltose). Conversely, fasted flies showed an increase in glutamate, α-ketoglutarate, tyrosine, and medium chain fatty acids, indicating higher catabolism of fatty acids, branched-chain amino acids, and ketone bodies for energy (Fig. 2a). Fasted flies also had changes in purine and pyrimidine catabolism, the urea cycle, and arginine and proline metabolism. We next used Flyscape to visualize changes in the tricarboxylic acid cycle (TCA cycle KEGG: dme00020) between refed and fasted fly bodies (Fig. 2b). The size of the compound nodes (hexagons) reflects changes in metabolite abundance between refed and fasted flies, (salmon-colored hexagons represent compounds that were not measured), and the green outlines highlight statistically significant measurements. While only acetyl-CoA, malate, and fumarate increased significantly, this visualization shows that nearly all compounds in the TCA cycle were higher in refed compared to fasted flies, while, α-ketoglutarate and glutamate were higher in fasted flies. Thus, Flyscape offers a contextualized visualization of the changes in cellular energetics between the two feeding states (Fig. 2b) compared to the differential displays of Fig. 2a. In our data, Flyscape reveals a change in the TCA cycle that is easy to appreciate: it is fueled by glucose in refed flies and by glutamate through α-ketoglutarate in fasted flies. Taken together these data provide evidence of a shift from β-oxidation/fatty acid metabolism and ketosis during the fasted state to increased glucose utilization after refeeding.

Fig. 2 The shifts in metabolic profiles in the bodies and heads of fasted and refed flies. a Heatmap of the 61 metabolites changed in the bodies of flies between the fasted and refed conditions; Welch’s t-test, FDR < 0.1. Normalized metabolite levels were clustered by compound (rows) and biological replicate (columns). The names of metabolites are colored according to their metabolic classes (bottom). The heatmap indicates positive (red shades) and negative (blue shades) normalized compound levels. b A Flyscape network showing the changes in the TCA cycle in the bodies of refed and fasted flies. The size of the compound nodes (hexagons) reflects changes in metabolite abundance (up or down) between refed and fasted flies, salmon-colored hexagons represent compounds that were not measured, and the green outlines highlight statistically significant measurements (Welch’s t-test, FDR < 0.1). c Heatmap of the top 61 (out of 159) metabolites that change in the heads of fasted and refed flies (Welch’s t-test, FDR < 0.1). Normalized compound levels were clustered by compound (rows) and data replicate (columns). The names of metabolites are colored according to their metabolic classes (bottom). The heatmap indicates positive (red shades) and negative (blue shades) normalized compound levels. d Flyscape network showing the metabolites changing in glycolysis, pentose-phosphate pathway, and TCA cycle in refed vs. fasted fly heads. The size of the compound nodes (hexagons) reflects changes in metabolite abundance between refed and fasted flies, red and salmon-colored hexagons represent compounds that were and were not measured, respectively, and the green outlines highlight statistically significant measurements (Welch’s t-test, FDR < 0.1). e Venn diagram showing the overlap in the metabolic shifts between the bodies of fasted and refed flies (lavender shade) and heads (green shade) of flies. Welch’s t-test, FDR < 0.1. Source data are provided as a Source Data file Full size image

We next asked if the metabolic profiles found in bodies also occurred in heads when flies were refed. Fly heads contain a multitude of tissue types, such as muscle and fat, but the majority of the head capsule is occupied by the brain’s ~150,000 neurons and glia. Of note, there was greater variation in the heads of refed compared to fasted flies, likely reflecting natural variation in food consumption between animals during the refeeding period (Supplementary Fig. 4b). Of the 391 compounds measured, 185 changed between the fasted and refed states in fly heads (Welch’s t-test, FDR < 0.1). The largest classes of compounds changed were lipids (85), amino acids (43), and carbohydrates (19) (Fig. 2c and Supplementary Data 1). Among the fats, we measured a large number of ether lipids, such as glycerophosphocholine (GPC) and glycero-3-phosphoryl ethanolamine (GPE), which are overrepresented in the fly and human brains25,26,27. Three times more compounds changed in heads between feeding states compared to bodies (159 vs. 61) and only 21 compounds were in common between the two (Fig. 2e). In contrast to bodies, all but three metabolites decreased with fasting in heads (Fig. 2c). Like the bodies, the metabolic profiles of refed heads showed higher glucose availability and increases in glucose-related products. However, heads had high-fold increases in glycolytic intermediates (KEGG: dme000103, phosphoglycerate, phosphoenolpyruvate) and end-products (lactate and pyruvate), and trends and increases in pentose-phosphate metabolites (KEGG: dme00030) indicating a differential and likely increased use of glucose (Fig. 2d). Glycogen intermediates were also increased suggesting higher glucose demand in heads. Higher levels of TCA cycle metabolites (citrate, aconitate, and α-ketoglutarate) and the pyruvate-acetyl CoA intermediate acetylphosphate suggest that carbon utilization into the TCA cycle may occur primarily from pyruvate derived from carbohydrate sources in the refed state (Fig. 2d). Finally, lipid metabolism was also rapidly altered by refeeding with increases in fatty acids as a class (Fig. 2c).

We also observed differences in neurotransmitters and their biosynthetic intermediates that were specific to heads (Supplementary Fig. 5). Gamma-aminobutyrate (GABA), glutamate, choline (the precursor for acetylcholine), and N-acetylserotonin were elevated in the heads of refed flies. In contrast, aspartate and N-acetylaspartate (NAA) were higher in fasted fly heads. γ-glutamylglutamine was also higher in fasted fly heads (Fig. 2c). This, together with the elevated levels of glutathione (Supplementary Fig. 5), may reflect higher oxidative stress in fasted fly heads (compared to bodies, where no change was observed). In conclusion, while both heads and bodies showed an increase in energy availability with refeeding, their metabolic profiles were largely non-overlapping, with higher glucose metabolism changes in heads.

Transcriptional changes in brains of sated and refed flies

Since we observed rapid and high magnitude variations in glucose metabolism in heads compared to bodies (Fig. 2), we wondered whether these metabolic changes could be supported by an increase in nutrient availability in this tissue, consistent with known changes in glucose in the hemolymph upon refeeding18,28. To probe this question, we measured changes in RNA abundance from the central brains of fasted and refed flies 1 h after feeding to allow for transcriptional responses to occur. To better focus on fast vs. slow responses to satiation, we also collected brains from flies that consumed their regular morning meal14 and were never fasted (here termed sated, see Methods). We identified 30 transcripts that changed in the central brains of refed/fasted flies (Fig. 3a, Supplementary Fig. 6a–c, Supplementary Data 2, FDR < 0.05 by Wald test) and 113 in sated/fasted flies (Fig. 3b, Supplementary Fig. 6a, d, e, Supplementary Data 2, FDR < 0.05 by Wald test). The RNA levels of sugar transporters and other S o l ute C arriers (SLC) homologues were higher in both refed and sated flies, while the transcript levels of the SLC17 (CG3036, Picot, CG6978), and SLC36 (CG7888) transporters higher in fasted brains. Fasted brains showed higher levels of lipases (brummer, CG5966) and branched-chain amino acid (CG1673) and purine metabolism (Gart and CG11089) (KEGG: dme00230). Refed brains had increases in enzymes for lipid (Lsd-1), neurotransmitter (CG12116), purine (Prat2), and folate metabolism (CG8665). Interestingly, only 11 transcripts overlapped between the refed and sated conditions (Fig. 3c, Supplementary Data 2), suggesting that while transcriptional responses to refeeding occur rapidly, they are also distinct from those of sated flies. With the exception of the Hormone receptor-like 38 (Hr38), transcription factors (Cabut29, fruitless, and doublesex) showed differential abundance only in sated flies. Overall these changes are consistent with the increase in catabolism of amino acids and nucleotides we observed in the metabolomics data and the higher availability of nutrients in refed flies. To see if any of the metabolite and RNA level changes were linked, we used Flyscape to integrate our head metabolomics and brain RNA-sequencing data by looking for significant genes and metabolites in the same network. This analysis connected the gene CG1673 to the conversion of the branched-chain amino acids (BCAA, leucine, valine, and isoleucine) and α-ketoglutarate to branched-chain keto acids (BCKA) (Fig. 3d). CG1673 RNA levels were higher in fasted brains and decreased with satiation, matching an increase in BCAA levels. Indeed, CG1673 is annotated as a branched-chain amino acid transaminase in Flybase, but has not been experimentally linked to a metabolic pathway. Our analysis supports the annotation of this gene and shows how the multi-omic feature of Flyscape can be used to identify and narrow down candidate genes, especially enzymes, to test with functional experiments. This, together with the availability of genome wide tools to modulate gene expression in Drosophila, will help to map specific metabolic pathways and study their function.

Fig. 3 RNA abundance changes of genes involved in nutrient transport and metabolism with refeeding. a, b Volcano plots showing the significant changes (Wald test, FDR < 0.05) in transcript levels between a refed vs. fasted and b sated vs. fasted brains. See main text and Methods for details on the feeding manipulations. The horizontal dotted line defines the p-value cutoff of 0.05, and the vertical lines indicate a log 2 fold change of ±1.5. Red circles indicate transcripts that pass p-value and log 2 fold cutoffs. c Venn diagram showing the overlap in the transcripts that change between the refed/fasted (purple shade) and the sated/fasted (pink shade) conditions. d A partial Flyscape network made using both the metabolomics (Fig. 2) and the RNA-sequencing data (this figure) showing the metabolites and genes that change between the fasted and refed conditions in branched-chain amino acid metabolism. The size of the compound nodes (red hexagons) reflects changes in metabolite abundance (up or down) between refed and fasted flies, and salmon-colored hexagons represent compounds that were not measured. The size of the gene nodes (blue circles) represent the sign of changes in RNA abundance between fasted and refed flies, (light blue circles are genes that were not measured). Green squares represent the enzyme type. Compounds with an FDR < 0.1 by Welch’s t-test and genes with a corrected p-value < 0.05 by Wald test are outlined in green. Source data are provided as a Source Data file Full size image

SD dulls metabolic transitions in fasted and refed flies

Since metabolite levels change depending on diet composition, we investigated the effects of a high sugar diet on the metabolic and behavioral transition between hunger and satiety. The influence of a high sugar diet on obesity, metabolic syndrome, and insulin resistance has been widely studied in Drosophila30,31; we also recently found that consumption of this diet decreases the sensitivity of the sweet gustatory neurons to sugar, which alters feeding patterns and promotes diet-induced obesity14.

We first examined the effect of a high sugar diet (SD, 30% sucrose) on the metabolome of the fasted and refed bodies compared to those of flies fed a control diet (CD, 5% sucrose). We observed 54/377 compounds changing in the refed state (CD/SD), and 149/381 compounds in the fasted state (CD/SD, Welch’s t-test, FDR < 0.1) (Fig. 4a, c; Supplementary Fig. 7a, b and Supplementary Data 1). Compounds in the lipid and energy categories were elevated in both fasted and refed SD bodies (Fig. 4b, d), including long and medium chain fatty acids (acyl-carnitines and triglycerides), glucose, lactate, and pyruvate. Consistent with this, flies on the SD had higher levels of triglycerides when these were measured using a colormetric assay (Supplementary Fig. 1c). Several amino acids and compounds known to increase in the plasma of fasted humans with obesity also increased in flies on a SD, such as, glutamate, α-ketoglutarate, cysteine, and aspartate32,33,34 (Supplementary Fig. 7). Metabolites in the hexosamine biosynthesis pathway were also elevated in both fasted and refed SD flies (Supplementary Fig. 7a, b). In contrast, the levels of acetyl-CoA and nucleotides were decreased on a SD compared to flies on a CD (Fig. 4b, d and Supplementary Fig. 7a, b). In accordance with this, we observed a decline in pentose-phosphate metabolites and an increase in ribose 5-phosphate, which may reflect changes in pentose-phosphate metabolism (KEGG: dme00030) with a high sugar diet (Supplementary Fig. 7a, b).

Fig. 4 Consumption of a SD alters the metabolic profiles of fasted and refed flies. a, b The effect of a high sugar diet on the metabolite classes (labeled by different colors) in the bodies of a, b refed and c, d fasted flies. Control diet (CD) and high sugar diet (SD). Welch’s t-test, FDR < 0.1. b, d The normalized levels of the compounds, grouped by class, that differ between b the refed CD and SD fly bodies (45 compounds), and d the fasted CD and SD fly bodies (144 compounds). Color scheme defines metabolite classes listed in a. e Venn diagram showing the overlap in the metabolic compounds that change between the refed and fasted conditions in the bodies of flies fed a CD (green shade) or SD (purple shade). Metabolites shared between flies on a CD and SD are listed and colored according to class as in color scheme from a. f A Flyscape network made by using compounds changed in bodies of refed flies fed a CD or SD (panels a and b in this figure) and RNA sequencing generated by another study (see main text and methods). The size of the compound nodes (red hexagons) reflects changes in metabolite abundance (up or down) between refed and fasted flies, and salmon-colored hexagons represent compounds that were not measured. The size of the gene nodes (blue circles) represent the magnitude of change in RNA abundance between fasted and refed flies, (light blue circles are genes that were no measured). Green squares represent the enzyme. Compounds with an FDR < 0.1 by Welch’s t-test and genes with a corrected p-value < 0.05 by Wald test are outlined in green. Source data are provided as a Source Data file Full size image

We next asked how a sugar diet influences the metabolic shift between hunger and satiety by comparing the metabolome of refed vs. fasted flies on a CD or SD. Principal component analysis of the bodies of flies on a SD revealed that two groups were well separated (Supplementary Fig. 4c). While biological replicates from each diet cluster together, the 95% confidence intervals overlap (lines), suggesting that a portion of the variance between the fasted and sated state is minimized when flies consume a high sugar diet. This is consistent with the finding that only 14 metabolites change between refed and fasted files on a SD (Fig. 4e), which is striking considering that 61 metabolites change in the bodies of refed and fasted flies fed a CD (Fig. 4e). To examine this phenomenon further, we considered the overall distribution of changes in abundance between the refed and fasted conditions (Supplementary Fig. 8a). The distribution is right shifted for CD, but centered at zero for SD, demonstrating that the changes in metabolite levels occurring during refeeding were essentially absent in the SD flies. Among the seven compounds that change independently of diet there are TCA cycle compounds, fumarate and malate and β-oxidation intermediates, 3-hydroxydecanoate and 3-hydroxyoctanoate (Fig. 4e). Refed SD bodies also showed a less robust increase in glycolysis upon refeeding, consistent with an increase in energy stores.

To better visualize the metabolic changes with the high sugar diet, we generated a Flyscape network comparing changes in TCA cycle metabolites in refed flies on a CD or SD (Fig. 4f) and plotted RNA-sequencing data generated from a previous study35 (Supplementary Fig. 9a–c, Supplementary Data 2; see Methods for differences in the diets). Flies on a SD showed increases in fumarate, malate, oxaloacetate glutamate, and α-ketoglutarate upon refeeding, but lower acetyl-CoA levels, suggesting a possible change in TCA cycle function in refed flies on a SD. Flyscape also identified a number of enzymes involved in these pathways whose RNA abundance was changed by diet35.

The effects of SD on feeding behaviors

Since fasted and refed flies on a SD have different body metabolic profiles compared to flies fed a CD, we examined its impact on acute feeding and foraging behaviors. To more carefully define the effects of diet exposure, we measured the feeding behaviors of age-matched male flies fed a CD or SD for 2, 5, and 7 days (SD2, SD5, and SD7). As in Fig. 1, we first fasted flies for 24 h, and then provided them with a meal of agar (fasted) or 400 mM D-glucose agar (refed) on the next day for 1 h (Supplementary Fig. 1a). We then assessed the effect of these manipulations on feeding behavior using the FLIC.

Fasted flies on a SD maintained their motivation to seek food (Supplementary Fig. 1b), which is consistent with the observation that diet had no effect on the percentage of refed or fasted flies eating on the FLIC (Fig. 5a). On both a CD and SD fasted flies had more feeding interactions and feeding events compared to refed flies (Fig. 5b, c), suggesting that the immediate responses to energy deprivation are maintained on a SD. However, fasted flies on a SD for 5 and 7 days interacted with their food less compared to fasted CD flies (Fig. 5b, SD2: P = 0.92, SD5: P = 0.95, 7D: P = 0.96 and Fig. 5c SD2: P = 0.84, SD5: P = 0.96, SD7: P = 0.93, posterior probability from Bayesian analysis), which is interesting, considering that SD flies have higher levels of energy and lipid metabolites and fewer metabolites changing between the fasted and refed states (14 vs. 61 metabolites, Fig. 4e). In addition, we find little difference in feeding event duration between fasted and refed (Fig. 5d). This suggests that the number of events drives the total feeding interaction, not event duration. Consequently, time between feeding events did not change dramatically between diets (Fig. 5e). However, a SD increased the time to initiate feeding (Fig. 5f). Thus, while flies on a high sugar diet still showed a clear behavioral response to fasting, this was smaller compared to that of CD flies, and the difference in feeding behaviors of hungry and sated flies was also decreased.

Fig. 5 SD changes the magnitude of the behavioral responses to fasting. The feeding behavior of 24 h-fasted (lighter shades) and previously refed (darker shades) flies during ad-libitum access to 5% sucrose on the FLIC for 1 h. Control diet, CD (green shade) and high sugar diet day 2, 5, and 7 (SD2, SD5, SD7, purple shades), (See Supplementary Fig. 1 for a schematic). For panels b–c, which were analyzed using a Bayesian model (see Methods for details), bars show the median value and extent of a 95% central interval on the population-level mean for samples from the posterior predictive distribution; stars are assigned for each of several comparisons based on the posterior probability from Bayesian analysis of a difference in the indicated direction: ***P > 0.999, **P > 0.99, *P > 0.95. Comparisons are performed for each timepoint’s fasted sample compared with the CD fasted sample, and for fasted vs. refed at each timepoint. For panels d–f, plotted bars show a bootstrap-based median and extent of a 95% confidence interval; **p < 0.01, *p < 0.05 using a stratified bootstrap; possible comparisons are identical to those in panels b, c. Fasted: CD n = 44, SD2 n = 38, SD5 n = 39, SD7 n = 31 biologically independent animals. Refed: CD n = 30, SD2 n = 34, SD5 n = 28, SD7 n = 29 biologically independent animals. a The percentage of fasted and refed flies that interacted with food on the FLIC (green or purple shades), compared to those that did not eat (gray shades). b–f The feeding behavior of flies during the 1-h ad-lib access to 5% sucrose quantified as b as the total number of feeding interactions; c the number of feeding events (defined as five of more consecutive feeding interactions above threshold); d the mean duration (sec) among feeding events; e the mean time between two or more feeding events (min); f the latency to interact with food (min), calculated as the first feeding interaction initiated on the FLIC. For panels d–f, replicates with no feeding events were excluded (for panels b, c the no-interaction events are explicitly accounted for in our zero-inflated negative binomial model). Source data are provided as a Source Data file Full size image

SD alters metabolic responses to fasting and refeeding

Since a sugar diet dulled the metabolic changes and blunted the magnitude of the behavioral transition between hunger and satiety states, we next investigated its effect on the metabolic profiles of heads. PCA showed that the variance between datasets was largely due to the feeding state, and the 95% confidence intervals are completely overlapping by SD7 (Supplementary Fig. 4d–f). First, we measured the number of metabolites changing between the fasted and refed state. On a control diet, 159 metabolites differed between the refed and fasted conditions (Fig. 2e); however, at 2, 5, and 7 days on a SD, 10, 33, and 0 metabolites, respectively, changed in heads between fasted and refed flies (Fig. 6a and Supplementary Data 1). These metabolites did not belong to a single class in particular; instead the metabolic difference between fasted and refed heads collapsed rapidly with consumption of a SD (Fig. 6a, blue bars). As with the body data, the distribution of fold changes in metabolite levels between refed and fasted conditions in heads on a CD was strongly right shifted, but centered on zero for flies fed a SD (Supplementary Fig. 8b). Interestingly, the differences in neurochemical levels between fasted and refed flies also disappeared when flies ate a SD (Supplementary Data 1).

Fig. 6 SD reshapes the metabolic transitions between hunger and satiety in fly heads. a The effects of short, (2 days, SD2), medium (5 days, SD5), and longer term (7 days, SD7) consumption of a high sugar diet (SD) compared to a control diet (CD) on the magnitude of the metabolite differences between the fasted and refed state on each diet. The size of the bars is proportional to the number of compounds in each metabolite category on the left. In blue are metabolites that were significantly different between fasted and refed flies in each condition (CD, SD2, SD5, and SD7 by Welch’s t-test, FDR < 0.1), and in gray metabolites that were not. b, c Projection onto the two most explanatory principal components for compound levels from b refed and c fasted heads of flies on CD (green) and fed a SD (purple shades) for 2 days (SD2), 5 days (SD5), or 7 days (SD7). The solid lines represent the 95% confidence interval, and percent explained variance is listed in parentheses. d, e Principal component loadings for the d refed and e fasted heads of flies fed a CD, or SD2, SD5, or SD7. Labels represent characteristic compounds. Source data are provided as a Source Data file Full size image

To examine how a high sugar diet alters the metabolite profile of fasted and refed state, rather than the transition between the two, we clustered compounds (refed 180 and sated 132, ANOVA FDR > 0.1) from heads that changed across CD, SD 2, 5, and 7 days (Supplementary Fig. 10 and Supplementary Fig. 11). We expected to find a pattern of smooth transitions where classes of metabolites gradually increased or decreased with longer exposure to diet. To our surprise, however, we found only a few gradual transitions (Supplementary Fig. 10a). In contrast, new metabolic profiles that characterize the fasted and refed states over different days on the SD emerged (Supplementary Fig. 10 and Supplementary Fig. 11). For example, less than half of the compound levels that define the refed state on a CD were maintained in the refed SD2 and SD5 flies (Supplementary Fig. 10b–d); instead, new refed metabolic profiles arose at 2 and 5 days (Supplementary Fig. 10e–g), but these were absent from the heads of SD7 refed flies (Supplementary Fig. 9b-e). Similarly, novel metabolic signatures were also present in the metabolic profiles of fasted SD fed flies (Supplementary Fig. 11a–d). It is particularly interesting to observe that some of these changes occurred after 2 days exposure to a SD and were maintained (Supplementary Fig. 10g), while others developed only at 7 days (Supplementary Fig. 10b).

To investigate whether the changes in metabolic signatures with short and longer exposure to the high sugar diet corresponded to transitions to distinct metabolic states, we conducted PCA in the refed and fasted conditions (Fig. 6b, c). We found that in each feeding state metabolites separated into four clusters defined by the time on the SD. Samples from SD2 and SD5 were largely overlapping, but entirely distinct from SD7 heads, suggesting that after long-term exposure to a high sugar diet, flies entered a different metabolic state. To identify which metabolites and pathways defined these new states, we examined the compounds that drive dominant patterns in PC1 and PC2 in the refed (Fig. 6d) and fasted (Fig. 6e) state. In the refed state, PC1 separated the metabolic profiles of SD7 heads, compared to other PCs. We used the compounds that contributed the most variation (PC1, top and bottom quartiles) for metabolic pathway network analysis. Compounds positively correlated with SD7 were enriched in aspartate metabolism (p < 2.2 × 10–4, FDR corrected hypergeometric test, SMPDB: SMP0000033), the urea cycle (p < 2.4 × 10−4, FDR corrected hypergeometric test, SMPDB: SMP0000059), TCA Cycle (p < 3.7 × 10−4, FDR corrected hypergeometric test, SMPDB: SMP0000057), glutamate metabolism (p < 1.0 × 10−3, hypergeometric test, SMPDB: SMP0000072) (Fig. 6d, Source Data). Methionine metabolism (p < 4.9 × 10−3, hypergeometric test, SMPDB: SMP0000033) and Phosphatidylcholine biosynthesis (p < 2.7 × 10−2, hypergeometric test, SMPDB: SMP0014306) were negatively correlated with the metabolic profiles of SD7 heads (Source Data). The fasted state datasets also clustered by PCA with time on diet, with SD2 and SD5 forming largely overlapping groups and CD and SD7 separating from the rest of the conditions (Fig. 6c). The fasted state in a CD is defined by higher levels of NAA, kynurenine, aspartate, γ-glutamyllysine, and tyrosine (Fig. 6e), which are depleted by both short- and long-term exposure to SD (Supplementary Fig. 11). Thus, these compounds are not only uniquely sensitive to feeding state (Fig. 2), but also responsive to overall energy levels. Overall, our analysis identifies a number of signature metabolites and pathways that are changed with exposure to a high sugar diet; together, this provides a starting point to investigate potential connections between metabolites levels, inter-organ communication, complex behaviors, and dietary environment.