1. Genetics and Genomics

Fat body phospholipid state dictates hunger-driven feeding behavior

  1. Kevin P Kelly
  2. Mroj Alassaf
  3. Camille E Sullivan
  4. Ava E Brent
  5. Zachary H Goldberg
  6. Michelle E Poling
  7. Julien Dubrulle
  8. Akhila Rajan  Is a corresponding author
  1. Basic Sciences Division, Fred Hutch, United States
  2. Cellular Imaging Core, Shared Resources, Fred Hutch, United States
https://doi.org/10.7554/eLife.80282
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Cite this article
  1. Kevin P Kelly
  2. Mroj Alassaf
  3. Camille E Sullivan
  4. Ava E Brent
  5. Zachary H Goldberg
  6. Michelle E Poling
  7. Julien Dubrulle
  8. Akhila Rajan
(2022)
Fat body phospholipid state dictates hunger-driven feeding behavior
eLife 11:e80282.
https://doi.org/10.7554/eLife.80282
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Abstract

Diet-induced obesity leads to dysfunctional feeding behavior. However, the precise molecular nodes underlying diet-induced feeding motivation dysregulation are poorly understood. The fruit fly is a simple genetic model system yet displays significant evolutionary conservation to mammalian nutrient sensing and energy balance. Using a longitudinal high-sugar regime in Drosophila, we sought to address how diet-induced changes in adipocyte lipid composition regulate feeding behavior. We observed that subjecting adult Drosophila to a prolonged high-sugar diet degrades the hunger-driven feeding response. Lipidomics analysis reveals that longitudinal exposure to high-sugar diets significantly alters whole-body phospholipid profiles. By performing a systematic genetic screen for phospholipid enzymes in adult fly adipocytes, we identify Pect as a critical regulator of hunger-driven feeding. Pect is a rate-limiting enzyme in the phosphatidylethanolamine (PE) biosynthesis pathway and the fly ortholog of human PCYT2. We show that disrupting Pect activity only in the Drosophila fat cells causes insulin resistance, dysregulated lipoprotein delivery to the brain, and a loss of hunger-driven feeding. Previously human studies have noted a correlation between PCYT2/Pect levels and clinical obesity. Now, our unbiased studies in Drosophila provide causative evidence for adipocyte Pect function in metabolic homeostasis. Altogether, we have uncovered that PE phospholipid homeostasis regulates hunger response.

Editor's evaluation

This manuscript posits that genetically-induced misregulation of phospholipid levels in fat cells causes defective hunger-driven feeding behaviors in adult Drosophila melanogaster. In parallel, the study also presents the rescue of feeding defects observed in diet-induced obese flies via the overexpression of the rate-limiting enzyme of phospholipid synthesis (PECT) in fly fat. This is an important paper that presents evidence of a potential causative relationship between phospholipid dysregulation and satiety sensing. This work will be of interest to a broad group of metabolism, obesity, and feeding behavior researchers.

https://doi.org/10.7554/eLife.80282.sa0

Introduction

Improper hunger-sensing underlies a multitude of eating disorders, including obesity (Suzuki et al., 2012). Yet, the cellular and molecular mechanisms governing the breakdown of the hunger-sensing system are poorly understood. In addition to lipid storage, adipocytes play a crucial endocrine role in maintaining energy homeostasis (Coelho et al., 2013; Kuryszko et al., 2016). Factors secreted by adipocytes impinge on several organs, including the brain, to regulate systemic metabolism and feeding behavior (Luo and Liu, 2016; Chatterjee and Perrimon, 2021; Brent and Rajan, 2020; Wurfel et al., 2022). Since lipids play a key role in signaling, adipocyte lipid composition is likely to regulate hunger perception and feeding behavior. Linking specific changes in adipocyte lipid composition to hunger perception and feeding behavior remains challenging.

While the effects of neutral fat reserves such as triglycerides on feeding behavior have been extensively studied (Cansell et al., 2014), less is known about the effects of phospholipids. Phospholipids comprise the lipid bilayer of the plasma membrane and anchor integral membrane proteins, including ion channels and receptors. They are essential components of cellular organelles, lipoproteins, and secretory vesicles (Shinoda, 2016). Changes to phospholipid composition can alter the permeability of cell membranes and disrupt intra- and intercellular signaling (Shinoda, 2016; Ben M’barek et al., 2017; Sunshine and Iruela-Arispe, 2017). Numerous clinical studies suggest an association between phospholipid composition and obesity (Sharma et al., 2013; Chang et al., 2019; Anjos et al., 2019). For example, insulin resistance, a hallmark of obesity-induced type 2 diabetes, is strongly associated with alterations in phospholipid composition (Chang et al., 2019). Additionally, key phospholipid biosynthesis enzymes are correlated with obesity in human genome-wide association studies (Sharma et al., 2013). Despite these intriguing possibilities, a causative link between altered phospholipid composition and metabolic dysfunction is yet to be established. Furthermore, whether altered adipocyte phospholipid composition specifically leads to dysfunctional hunger-sensing is unknown.

Phosphatidylethanolamine (PE) is the second most abundant phospholipid and is essential in membrane fission/fusion events (Vance, 2015; Moon and Jun, 2020; Emoto and Umeda, 2000). PE is synthesized through two main pathways in the endoplasmic reticulum (ER) and the mitochondria (Farine et al., 2015). Phosphatidylethanolamine cytidylyltransferase (Pcyt/Pect) is the rate-limiting enzyme of the ER-mediated PE biosynthesis pathway (Dobrosotskaya et al., 2002). Global dysregulation in Pcyt/Pect activity has been shown to cause metabolic dysfunction in animal models and humans (Lim et al., 2011; Tsai et al., 2019). For example, Pyct/Pect deficiency in mice causes a reduction in PE levels, leading to obesity and insulin resistance (Fullerton et al., 2009). Similarly, human studies have found that obese individuals with insulin resistance have decreased Pcyt/Pect expression levels (Yang et al., 2002). Chronic exposure to a high-fat diet causes upregulation of Pcyt/Pect, associated with increased weight gain and insulin resistance (de Wit et al., 2008). These findings suggest that disruptions in Pcyt/Pect activity, and consequently PE homeostasis, are a common underlying feature of obesity and metabolic disorders. What remains largely unknown is whether Pcyt/Pect activity in the adipose tissue directly regulates insulin sensitivity and feeding behavior.

Like humans, chronic overconsumption of a high-sugar diet (HSD) results in insulin resistance, diet-induced obesity (DIO), and metabolic imbalance in flies (van Dam et al., 2020; Smith et al., 2014; Arrese and Soulages, 2010; Gáliková and Klepsatel, 2018; Musselman et al., 2011; Walker et al., 2017). There is deep evolutionary conservation of feeding neural circuits regulating feeding behavior between flies and mammals (Pool and Scott, 2014; Kim et al., 2017; Krashes et al., 2009; Beshel and Zhong, 2013; Wu et al., 2003), and multiple studies on feeding behavior in Drosophila have identified key neurons and receptors involved (Musso et al., 2019; Musso et al., 2021; Stanley et al., 2021; Lin et al., 2022; Chen and Dahanukar, 2017; Dus et al., 2015). Furthermore, like humans, Drosophila display altered feeding behavior in response to highly palatable foods (Kim et al., 2021; Tennessen et al., 2014; May et al., 2019; Small, 2009; Volkow et al., 2011). Additionally, given flies’ short lifespan, feeding behavior in response to an obesogenic diet can be monitored throughout the adult fly’s lifespan, providing temporal resolution of behavioral changes under DIO (Ro et al., 2014; Pendergast et al., 2017; Pendergast et al., 2014; Deshpande et al., 2014; Post et al., 2019). Thus, using a chronic HSD feeding regime in adult flies allows for discovering specific mechanisms relevant to human biology.

In this study, we assess the effects of chronic HSD consumption on flies’ hunger-driven feeding (HDF) behavior across a 28-day time window. We note that while HSD-fed flies maintain their ability to mobilize fat stores on starvation, they lose their HDF response after 2 weeks of HSD treatment, suggesting an uncoupling of nutrient sensing and feeding behavior. We reveal that changes in phospholipid concentrations in HSD-fed flies occur during HDF loss. We further show that genetic disruption of the key PE biosynthesis enzyme Pect in the fat body, the fly’s adipose tissue, results in the loss of HDF even under normal food (NF) conditions. Significantly, Pect overexpression in the fat body is sufficient to protect flies from HSD-induced loss in HDF. Our data suggest that adipocyte PE-phospholipid homeostasis is critical to maintaining insulin sensitivity and regulating hunger response.

Results

Exposure of adult Drosophila to HSDs for 14 days disrupts HDF

To assess how obesogenic diets alter HDF, we developed a feeding paradigm using a quantitative monitor (Fly Liquid Interaction Counter [FLIC]) to assess feeding activity over time on different diets (Figure 1A). In brief, wild-type (w1118) flies were housed in vials containing NF or HSD (30% more sucrose than NF). After exposure to NF or HSD for 5–28 days, flies were subject to a 0% sucrose/agar media (starvation – stv media) for 16 hr to induce hunger. After 16 hr of starvation, we monitored flies’ feeding behavior using the FLIC (Ro et al., 2014) for 3 hr (see Figure 1A and ‘Methods’). We observed that NF-stv w1118 flies showed increased feeding compared to flies fed ad libitum (NF-fed) (Figure 1B, Figure 1—figure supplement 1), which is consistent with an HDF response in vertebrates (Ellacott et al., 2010; McGrath et al., 2019). However, HSD-fed flies, though they displayed an HDF response on days 3–10 of HSD exposure, showed a progressive loss of the HDF response to starvation starting on day 14 (Figure 1C, shaded in yellow, and Figure 1—figure supplement 1A). Excluding the possibility that the loss in HDF is due to increased baseline feeding on HSD, flies on NF and HSD showed similar ad libitum feeding behavior (Figure 1D), suggesting that beyond day 14, HSD hunger-sensing is altered.

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High-sugar diet (HSD) causes progressive loss in hunger-driven feeding (HDF).

(A) HDF behavior in flies was tested using the schematic in (A). After aging flies for 7 days on normal lab food, flies we subject to a normal diet or an HSD (30% more sugar in food) for a duration of 3–28 days. For every timepoint, hunger was induced by subjecting flies to starvation (agarose, 0% sucrose media) overnight for 16 hr. Quantitative feeding behavior was monitored using the Fly Liquid Interaction Counter (FLIC) during a 3 hr window immediately after the starvation period. (B) Average feeding events over time for normal food (NF) flies that were either fed (filled circles) or starved for 16 hr prior to measurement (stv; no fill). Note that HDF is maintained throughout the experiment. (C) Average feeding events over time for HSD-fed flies that were either fed or starved for 16 hr prior to measurement (stv). Note the loss of HDF on day 14. (D) Comparison of basal feeding in NF and HSD fed flies over time. N = 18 for each treatment and timepoint. (E, F) Average triacylglyceride (TAG) levels per fly of NF (E) and HSD-fed (F) flies at baseline and after 16 hr of starvation. (G) Average change in TAG levels after starvation in NF and HSD flies (n = 8–9 for each treatment and timepoint). (H) Flies given HSD for 14 days were starved for various durations on 0% sucrose media (16, 20, 24, and 32 hr, respectively) with feeding events recorded as in (B–D) (n = 6–20 for each treatment). Starvation periods were staggered such that all flies were assayed on the FLIC at the same time. (I) Average TAG levels per fly of (H) flies after subjected to starvation of various durations (n = 4 for each treatment). (J) TAG levels per fly of (H) flies normalized to the HSD fed control. Two-way ANOVA with Sidak post-test correction. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation.

Figure 1—source data 1

w1118 hunger-driven feeding responses related to Figure 1B–D.

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Figure 1—source data 2

Change in w1118 triacylglyceride (TAG) levels after 16 hr of starvation related to Figure 1E–G.

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Figure 1—source data 3

w1118 hunger-driven feeding responses on high-sugar diet (HSD) related to Figure 1H.

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Figure 1—source data 4

Triacylglyceride (TAG) levels of 14-day high-sugar diet (HSD)-fed w1118 flies related to Figure 1I.

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Figure 1—source data 5

Normalized triacylglyceride (TAG) levels of 14-day high-sugar diet (HSD)-fed w1118 flies related to Figure 1J.

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We then wondered whether HSD-fed flies were capable of sensing and responding to starvation by breaking down energy reserves. Triacylglycerides (TAGs) are the largest energy reserve and are mobilized when flies are starved (Heier and Kühnlein, 2018). Thus, changes in TAG levels following starvation can be used as a readout for cellular energy-sensing in Drosophila (Hildebrandt et al., 2011; Heier et al., 2021). We observed that HSD-fed flies displayed similar levels of starvation-induced TAG breakdown to NF-fed flies throughout the 4-week window (Figure 1E–G), suggesting that starvation-induced lipolysis remains functional in HSD-fed flies. Even though starvation-induced TAG mobilization in HSD-fed flies is intact throughout the 4-week time window (Figure 1E–G), the HDF response only dampens after 14 days of HSD (Figure 1C). Overall, this suggested that while flies maintain HDF up to 10 days of HSD exposure, starting at 14 days of HSD, there is a loss of hunger response. However, an alternative hypothesis is that fatter flies (Figure 1—figure supplement 2) have delayed hunger perception due to the extra levels of stored energy and, therefore, a delayed need for food and would need to be starved longer to become hungry. To test this, 14-day HSD-fed flies were starved for a range of fasting times (16–32 hr) and then assayed for HDF. We observed that at 16, 24, and 32 hr of starvation, flies do not display HDF (Figure 1H). At 24 and 32 hr of starvation, HSD-fed flies broke down 50% of their fat stores (Figure 1I and J). At 24 and 32 hr, flies do not display increased feeding in response to this significant energy deficit (Figure 1H–J). Notably, although 5–10-day HSD-fed flies have comparable TAG levels to 14-day HSD-fed flies (Figure 1F), they display a robust hunger response within 16 hr of starvation (Figure 1C, Figure 1—figure supplement 1). In contrast, at 14 days of HSD exposure, even at 32 hr of starvation, when flies break down >50% of TAG stores (Figure 1I and J), they do not display a robust and sustained hunger response (Figure 1H). Hence, subjecting flies to a 14-day HSD disrupts their HDF regardless of TAG stores and fasting time.

Insulin resistance and lipid morphology changes at the point of HDF loss

The loss of HDF behavior after 14 days of HSD suggests that this is a critical timepoint of metabolic disruption. Given that insulin signaling is a major regulator of systemic metabolism (Kleinridders et al., 2014; Petersen and Shulman, 2018) and insulin resistance is a hallmark of obesity (Wu and Ballantyne, 2020), we asked whether HSD-fed flies display dysfunctional insulin signaling. To answer this, we first measured the amount of Drosophila insulin-like peptide 5 (Dilp5) accumulation in the brain’s insulin-producing cells (IPCs). It has been shown that Dilp5 accumulation in the IPCs directly correlates with nutritional status (Géminard et al., 2009); when flies experience a nutrient-rich environment, Dilp5 levels in the IPCs drop due to increased insulin secretion (Pasco and Léopold, 2012). Consistent with the previous reports (Pasco and Léopold, 2012), we found that 14 days of HSD feeding ad libitum resulted in decreased Dilp5 accumulation in the IPCs (Figure 2A). To determine the downregulation of Dilps at the transcript level, we analyzed the expression of the IPC-secreted Dilps 2 and 5 (Rulifson et al., 2002). We found that 14 days of HSD treatment did not alter the expression of Dilps 2 and 5 (Figure 2—figure supplement 1). These results (Figure 2A, Figure 2—figure supplement 1) suggest that HSD increases Dilp5 secretion.

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Drosophila insulin-like peptide 5 (DILP5)/forkhead box O (FOXO) accumulation and lipid droplet morphology altered under high-sugar diet (HSD) exposure.

(A, left) Representative confocal images of Dilp5 accumulation in insulin-producing cells (IPCs) of normal food (NF) flies (top panel) and HSD-fed flies on day 14 (bottom panel). (A, right) Mean Dilp5 fluorescent intensity from z-stack summation projections of IPCs from NF and HSD-fed flies. N = each square represents a single fly. All data were collected from a single experiment. Unpaired t-test with Welch’s correction. (B) Representative confocal images of nuclear FOXO accumulation in the fat bodies of NF flies (top panel) and HSD-fed flies on day 14 (bottom panel). The nuclei are marked with anti-lamin (magenta). Arrowheads point to nuclei. (B, right) Mean nuclear FOXO fluorescent intensity from z-stack summation projections of fat bodies from NF and HSD-fed flies. N = each circle represents a nucleus. All data were collected from a single experiment. Two-sided Wilcoxon rank-sum test. Error bars = standard deviation. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. (C) Representative confocal images of lipid droplets (magenta) across time in the fat bodies of NF and HSD-fed flies.

Figure 2—source data 1

Drosophila insulin-like peptide 5 (Dilp5) accumulation in insulin-producing cell (IPC) after 14 days on normal food (NF)/high-sugar diet (HSD).

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Figure 2—source data 2

Forkhead box O (FOXO) accumulation in w1118 (14 days after diet treatment).

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We reasoned that, as previously reported (Musselman et al., 2011), the changes in insulin signaling may lead to insulin resistance in peripheral tissue. To address this, we measured the fat body’s forkhead box O (FOXO) nuclear localization (Figure 2B). Insulin signaling is activated by insulin binding to its cell surface receptor (IR) (Brogiolo et al., 2001; Böhni et al., 1999). When insulin activates IR, it triggers a phosphorylation cascade of multiple downstream targets, including the transcription factor FOXO (Kramer et al., 2003; Teleman et al., 2005). Phosphorylation of FOXO prevents it from entering the nucleus and initiating the gluconeogenic pathway, a starvation response pathway. Thus, FOXO nuclear localization has been used as a proxy to monitor insulin sensitivity (Lee and Dong, 2017; Gross et al., 2008). Since the fat body is a major target for insulin signaling (Tain et al., 2021), we wondered whether increased insulin signaling in HSD led to insulin resistance. Indeed, we found that 14 days of HSD treatment resulted in elevated nuclear FOXO levels compared to the NF treatment. Notably, this effect was not seen after acute 6-hr exposure to HSD (Figure 2—figure supplement 2).

Accumulation and enlargement of lipid droplets, the cell’s lipid storage organelles, are associated with insulin resistance (Kim et al., 2015). Flies on HSD showed progressively larger, misshapen, and denser lipid droplets than flies on NF (Figure 2C). Thus chronic 14-day HSD treatment reduces Dilp5 in the IPCs, increases nuclear localization of FOXO in the fat body, and alters lipid droplet morphology; all these changes are consistent with the onset of insulin resistance.

Lipidomics on HSD uncovers alterations in whole-body phospholipid levels at 14-day HSD

Next, we sought to characterize the progressive changes in the lipidome of flies subjected to HSD using a targeted quantitative lipidyzer (see ‘Methods’). Seven-day exposure to HSD did not significantly change the overall concentrations of lipid classes (Figure 3, Figure 3—figure supplement 1). But a prolonged 14-day exposure significantly increased TAGs and diacylglycerides (DAGs) (Figure S4A). At the same time, free fatty acids (FFAs) were surprisingly lower in HSD-fed flies than in NF (see ‘Discussion’). Intriguingly, prolonged 14-day exposure to HSD caused a significant increase in the PE and phosphatidylcholine (PC) levels (Figure 3). We also observed that two other minor phospholipid classes – lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE)— are downregulated on 14-day HSD. In particular, LPE downregulation was statistically significant (Figure 3). We speculate that LPE reduction likely affects upregulated PE synthesis as LPE serves as a precursor for PE (Riekhof and Voelker, 2006; see ‘Discussion’). These findings indicate that altered phospholipid levels correlate with HDF loss and insulin resistance.

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Phospholipids are elevated in whole fly during extended high-sugar diet (HSD) feeding.

Average concentrations of phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), and lysophosphatidylethanolamine (LPE) in flies subjected to normal food (NF) (green) or an HSD (red) for 14 days. Lipidomics was performed using a targeted quantitative lipidyzer (Sciex 5500 Lipidyzer). Ten independent biological replicates were used for each diet and each day, with n = 10 flies composing one biological replicate. Two-way ANOVA and Sidak post-test correction. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation.

Figure 3—source data 1

Lipidomics data for lipid classes of normal food (NF) and high-sugar diet (HSD)-fed flies on day 7 presented in Figure 3 and Figure 3—figure supplement 1.

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Figure 3—source data 2

Lipidomics data for lipid classes of normal food (NF) and high-sugar diet (HSD)-fed flies on day 14 presented in Figure 3 and Figure 3—figure supplement 1.

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Fat body Pect levels regulate apolipoprotein delivery to the brain

PC and PE are primarily synthesized by the fat body and trafficked in lipophorin particles (Lpps) chaperoned by ApoLpp to other organs, including the brain (Palm et al., 2012). ApoLpp is the functional ortholog of human ApoB (Palm et al., 2012). In flies, Apolpp is post-translationally cleaved into ApoI and ApoII. ApoII is the fragment of Apolpp that harbors the lipid-binding domain. PE-rich ApoII particles have been shown to traffic from fat to the brain (Palm et al., 2012). Since PE levels are elevated after 14 days of HSD treatment (Figure 3), we predicted increased ApoII levels in the brain. Using an antibody generated against ApoII (Figure 4—figure supplement 1), we asked whether 14 days of HSD treatment would increase ApoII delivery to the brain. Surprisingly, we found that though HSD treatment caused an increase in the overall PC and PE lipid levels (Figure 3), the amount of ApoII that chaperones PE to the brain was significantly reduced in an area of the brain proximal to the IPCs (Figure 4A). This observation suggests that fat-to-brain trafficking of PE via ApoII particles is disrupted after 14 days of HSD (see ‘Discussion).

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High-sugar diet (HSD) and knockdown of Pect lead to decreased ApoII levels in the brain.

(A–C, left) Representative confocal images of ApoII (red) levels in the insulin-producing cells (IPCs) (blue) of (A) normal food (NF) and HSD-fed flies on day 14, (B) flies with a fat-specific knockdown of Luc, eas, and Pect, and (C) flies with a fat-specific overexpression of Luc and Pect. (A–C, right) Mean number of ApoII puncta and % area covered by ApoII puncta in the IPCs of (A) NF and HSD-fed flies on day 14, (B) flies with a fat-specific knockdown of Luc, eas, and Pect, and (C) flies with fat-specific overexpression of Luc and Pect. N = each square represents a single fly. All data were collected from a single experiment. Unpaired t-test with Welch’s correction. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation.

Figure 4—source data 1

ApoII accumulation in the insulin-producing cells (IPCs) of normal food (NF) and high-sugar diet (HSD)-fed w1118 flies.

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Figure 4—source data 2

ApoII accumulation in the insulin-producing cells (IPCs) of phosphatidylethanolamine (PE) knockdown flies.

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Figure 4—source data 3

ApoII accumulation in the insulin-producing cells (IPCs) of Pect overexpression flies.

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ApoLpp is synthesized exclusively by the fat body, and Lpps are enriched in PE (Palm et al., 2012). Hence, we hypothesized that altering the PE biosynthesis pathway genetically, via RNAi-mediated knockdown, of the crucial enzymes Pect and easily shocked (eas) (Lim et al., 2011; Tsai et al., 2019; Nyako et al., 2001) would affect ApoII levels in the brain. Using qPCR, we validated the efficiency of Pect knockdown (Figure 6—figure supplement 1A). We found that while eas did not alter the levels of ApoII in the brain, Pect, the rate-limiting enzyme of PE biosynthesis, caused a reduction in ApoII levels like that of HSD (Figure 4B). Conversely, fat body-specific Pect overexpression increased ApoII levels in the brain (Figure 4C). Given that HSD and Pect knockdown caused a similar effect on ApoII levels in the brain, we predicted that Pect mRNA levels would be low in the HSD-fed flies. To our surprise, we found that 14 days of HSD caused a 200- to 270-fold rise in Pect mRNA levels that fell sharply by day 21 (Figure 6—figure supplement 1B) compared to the modest ~7-fold increase in the Pect OE flies (Figure 6—figure supplement 1A, right). Hence, extreme deregulation of Pect levels, either up or down, may affect PE levels and their carrier ApoII (see ‘Discussion’). This interpretation is consistent with previous studies linking Pect dysregulation to abnormal lipid metabolism and signaling (Fullerton et al., 2009; Yang et al., 2002; de Wit et al., 2008).

Fat body-specific Pect knockdown shows FOXO accumulation and lipid morphology changes similar to HSD

Given that PE homeostasis is disrupted under HSD (Figure 3), which coincides with signs of insulin resistance in the fat body (Figure 2B and C), we asked whether fat body-specific knockdown of Pect affects insulin sensitivity. Therefore, we measured the nuclear FOXO levels of fat body-specific Pect knockdown flies (Figure 5A). We found that, like the HSD-treated flies (Figure 2B), Pect knockdown flies exhibit increased nuclear localization of FOXO. Since lipid droplets serve as a repository for lipids (Yu and Li, 2017), the building blocks of phospholipids, we reasoned that knocking down Pect will lead to excessive accumulation of lipids and result in enlarged lipid droplets resembling flies on HSD. Indeed, a qualitative view of lipid droplets in Pect knockdown flies showed larger and more clustered lipid droplets than in control (Figure 5B). These data suggest that Pect is important for mediating insulin sensitivity in the fat body, and its loss leads to DIO-like phenotypes.

Figure 5
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Pect knockdown in fly fat alters forkhead box O (FOXO) nuclear accumulation and lipid droplet morphology.

(A, left) Representative confocal images of Lpp-Gal4>UAS-Luc-RNAi and Lpp-Gal4>UAS-Pect-RNAi fly fat immunostained with anti-FOXO antibody (blue to green, intensity-based) and lamin (pink) on day 14. Arrowhead points to the nucleus. (A, right) Mean nuclear FOXO fluorescent intensity of fat bodies from control (LppGal4>UAS-Luc-RNAi) and fat-specific Pect knockdown flies (LppGal4>UAS-Pect-RNAi). N = each circle represents a nucleus. All data were collected from a single experiment. Two-sided Wilcoxon rank-sum test. Error bars = standard deviation. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation. (B) Representative confocal images of lipid droplets (magenta) in the fat bodies of control (LppGal4>UAS-Luc-RNAi) and fat-specific Pect knockdown flies (LppGal4>UAS-Pect-RNAi). Note that lipid droplet morphology in the fat-specific Pect knockdown flies resembles that of wild-type flies on high-sugar diet (HSD).

Figure 5—source data 1

Nuclear forkhead box O (FOXO) accumulation in LppGal4>Pect-RNAi fat.

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Pect knockdown in the fat body alters whole-body phospholipid concentrations

Next, we sought to determine the impact of Pect on the lipidome of adult flies. We compared the lipidomic profile of whole flies expressing Pect-RNAi using a fat-specific driver (Lpp-Gal4) against a control-RNAi (luciferase-RNAi; Figure 6). We found that knocking down Pect in the fat body slightly reduced whole-body PE levels (Figure 6A). Our results are consistent with a previous study showing that Pect null mutants did not display significant alterations in the levels of PC and PE (Tsai et al., 2019). Again, consistent with the same study (Tsai et al., 2019), we observed that specific PE species showed significant alterations, with PE 36.2 displaying a significant downregulation (Figure 6B; see ‘Discussion’).

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Manipulating Pect levels in the fat body alters phospholipid profile.

(A) Average concentrations of phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), and lysophosphatidylethanolamine (LPE) lipid classes in LppGal4>UAS-Pect-RNAi flies compared to control under 7-day normal food (NF) conditions. (B) Depicts the concentration of Pect-associated phospoholipids in LppGal4>UAS-Pect-RNAi flies compared to control. Lipidomics was performed using a targeted quantitative lipidyzer (Sciex 5500 Lipidyzer). 4–6 independent biological replicates were used for each genotype, with n = 10 flies composing one biological replicate. Unpaired t-test with Welch’s correction. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation, points = individual replicate values.

Figure 6—source data 1

Lipidomics for fat-specific Pect knockdown and Pect overexpression on normal food.

Relevant to Figure 6, Figure 6—figure supplements 2–4.

https://cdn.elifesciences.org/articles/80282/elife-80282-fig6-data1-v2.xlsx

Furthermore, while other major lipid classes did not significantly deviate from control (Figure 6—figure supplement 3), we noted a striking and significant increase in two minor classes of phospholipids, LPC and LPE (Figure 6A). Given that LPE can serve as a precursor for PE via the exogenous lysolipid metabolism (ELM) pathway (Riekhof and Voelker, 2006), we speculate that in the absence of the rate-limiting enzyme for PE synthesis, there is an elevation in LPE levels (see ‘Discussion’). We also performed the same analysis in a Pect overexpression fly line but found no change in any lipid classes compared to the control (Figure 6—figure supplement 4). Together, this suggests that fat-specific knockdown of Pect is sufficient to cause a reduction in certain PE species and upregulation of the minor phospholipid classes, especially the PE precursor class of minor phospholipid LPE. Hence, we conclude that fat body-specific Pect disruption results in systemic phospholipid class composition imbalance.

Pect knockdown in the fat modulates HDF behavior

We next sought to determine whether phospholipid imbalance can impact feeding behavior. Given that the fat body is a major source of phospholipids synthesis (Palm et al., 2012), we asked whether disrupting PE and PC synthesis would impact HDF behavior in NF and HSD feeding conditions. To answer this, we knocked down key enzymes in the fat body’s PE and PC biosynthesis pathways and assessed HDF behavior in response to starvation when flies are fed NF (Figure 7A). Note that for the starvation experiments in these UAS/Gal4 conditions, we observed lethality on a 0% sucrose diet. Hence, we used a low-nutrient diet (1% sucrose agar) to induce nutrient deprivation (see ‘Methods’). We found that knocking down the PC-biosynthesis enzyme Pyct2 did not affect HDF (Figure 7A). Similarly, the knockdown of eas, which initiates the early enzymatic reaction of PE biosynthesis (Nyako et al., 2001), did not influence HDF (Figure 7A). However, knocking down the rate-limiting enzymes in the ER (Pect) and mitochondria (PISD)-mediated PE biosynthesis pathways (Zhao and Wang, 2020) led to a diminished HDF response even on normal diets (Figure 7A). Our results are consistent with a critical role for PE enzymes in regulating HDF behavior even under a normal diet.

Figure 7
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Manipulating Pect levels in the fat body alters hunger-driven feeding behavior.

(A) A simplified schematic of the phosphatidylethanolamine (PE) and phosphatidylcholine (PC) biosynthesis pathway. eas and Pect are enzymes in the PE biosynthesis pathway, whereas PCYT2 is an enzyme in the PC biosynthesis pathway. (A, top) Average fly feeding events over time for normal food (NF) flies that were either fed or starved using a 1% sucrose agar diet (stv) for 16 hr prior to measurement. (A, bottom) Average feeding events over time for high-sugar diet (HSD)-fed flies that were either fed or starved for 16 hr prior to measurement using a 1% sucrose agar diet (stv). (B) Average feeding events of fed and starved Lpp-Gal4>Pect-overexpression on NF (left) and HSD (right) at 7 and 14 days of diet treatment. Each dot denotes an individual fly. Asterisks indicate significant changes with p-value<0.05, p-value<0.005, and p-value<0.0005. Error bars = standard deviation. For (A) and (B), each dot denotes an individual fly. Two-way ANOVA with Sidak post-test correction.

Figure 7—source data 1

Day 14 feeding behavior in phosphatidylethanolamine (PE)/phosphatidylcholine (PC) biosynthesis enzymes fat-specific knockdown flies relevant to Figure 7A.

https://cdn.elifesciences.org/articles/80282/elife-80282-fig7-data1-v2.xlsx
Figure 7—source data 2

Pect fat-specific overexpression of hunger-driven feeding behavior (normal food [NF] and high-sugar diet [HSD]) relevant to Figure 7B.

https://cdn.elifesciences.org/articles/80282/elife-80282-fig7-data2-v2.xlsx

Interestingly, the knockdown of eas, PISD, and Pect all led to a loss of HDF on HSD treatment (Figure 7A, lower panel). We measured HDF response in 14-day HSD-fed flies with fat body-specific Pect overexpression (Pect OE). These flies maintained a hunger response on HSD (Figure 7B). Since 14 days of HSD exposure is a critical timepoint for HDF breakdown in the wild-type flies (Figure 1C and H), this suggests that adipocyte Pect activity regulates hunger response. Consistent with our findings that 14-day HSD-fed flies show defective hunger response independent of TAG store levels (Figure 1F, I and J), we found that Pect knockdown does not alter baseline TAG store levels (Figure 6—figure supplement 3) but disrupts hunger response (Figure 7A). Together, these results show that Pect activity in the adult fly adipocytes is critical for regulating hunger response.

Discussion

Several studies have shown a link between chronic sugar consumption and altered hunger perception (Penaforte et al., 2013; Prinz, 2019). Although the neuronal circuits governing hunger and HDF behavior have been well studied (Lin et al., 2019), less is known about the impact of adipose tissue dysfunction on feeding behavior. Using a Drosophila DIO model, we show that phospholipids, specifically PE, play a crucial role in maintaining HDF behavior.

The Drosophila model organism is a relevant model for human DIO and insulin resistance (Kim et al., 2021). Studies from Dus and Ja et al. have previously performed measurements on taste preference, feeding behavior/intake, survival, etc., using an HSD-induced obesity model, and have found much in common with their mammalian counterparts (May et al., 2019; Deshpande et al., 2014). However, the longest measurement of adult feeding behavior has been capped at 7 days (van Dam et al., 2020). A recent study by Musselman and colleagues analyzed the fly lipidome on 3-week and 5-week HSD in a tissue-specific manner (Tuthill et al., 2020) and identified changes in neutral fat stores in the cardiac tissue (Tuthill et al., 2020).

In this study, we defined that a 14-day exposure of adult Drosophila to an HSD regime disrupts hunger response (Figure 1C and H). On evaluating HSD regime-induced lipid composition changes at this critical 14-day point, we uncovered a critical requirement for adipocyte PE homeostasis and a fat-specific role for the PE enzyme Pect in controlling HDF (Figure 7). Pect function in the adult fly adipocytes is critical for appropriate fat-to-brain lipoprotein delivery (Figure 4) and the maintenance of systemic insulin sensitivity (Figure 5). In sum, we identify that adipocyte-specific loss of Pect phenocopies the metabolic dysfunctions observed in a chronic HSD regime in adult flies. Therefore, we propose that PE homeostasis, specifically Pect activity in fat tissue, regulates HDF response (Figure 8).

Figure 8
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Pect function in adult fly adipocytes regulates hunger response.

We identify that fat-specific knockdown of the rate-limiting phosphatidylethanolamine (PE) synthesis enzyme, Pect, even on normal diet, phenocopies the metabolic effects of subjecting flies to chronic (>14 days) high-sugar diet. We show that Pect function, in the adult fly adipocytes, is required for appropriate hunger response (top panel), insulin signaling, and fat to brain lipoprotein delivery (lower panel). We find that fat body-specific Pect overexpression can prolong appropriate hunger response on high-sugar diets (green box, upper panel).

HSD leads to insulin resistance and a progressive loss of HDF behavior

Changes in feeding behavior in both vertebrates and invertebrates occur via communication between peripheral organs responsible for digestion/energy storage and the brain (Prinz, 2019). This communication is facilitated by factors that provide information on nutritional state (Ahima and Antwi, 2008). One example of such a factor is leptin, released from the adipose tissue and acts on neuronal circuits in the brain to promote satiety (Rajan and Perrimon, 2012; Friedman and Halaas, 1998). While leptin has long been studied as a satiety hormone, recent work in mice and flies suggests that a key function of leptin and its fly homolog upd2 regulates starvation response (Brent and Rajan, 2020; Rajan and Perrimon, 2012; Ahima et al., 1996; Huang et al., 2020). Indeed, we have previously shown that exposing flies to HSD alters synaptic contacts between Leptin/Upd2 sensing neurons and Insulin neurons. However, it resets within 5 days (Brent and Rajan, 2020), suggesting that yet-to-be-defined mechanisms maintain homeostasis on surplus HSDs beyond 5 days.

We analyzed feeding behavior over time to delineate how HSD alters the starvation response. We found that under normal diet conditions flies display a clear response to starvation in the form of elevated feeding that we termed ‘hunger-driven feeding (HDF),’ which was independent of age (Figure 1B). In contrast, chronic exposure to HSD led to a progressive loss of HDF that began on day 14 (Figure 1C). It could be argued that loss of HDF is simply due to an elevation of TAG storage in HSD-fed flies (Figure 1—figure supplement 2), thus losing the need to feed on starvation. However, several pieces of evidence support the idea that HSD affects feeding behavior independently of nutrient sensing. Under our experimental conditions, we find basal feeding to be statistically similar between NF-fed and HSD-fed conditions at all timepoints with the exception of day 10 (Figure 1D). Note that Dus and colleagues reported that on a 20% sucrose liquid diet for 7 days elevated food interactions (May et al., 2019, May et al., 2020). However, the Dus et al. studies are not comparable with our study due to the large differences in experimental protocol. They evaluated taste preference changes and feeding interactions on 5–30% sucrose liquid diet in 24-hr window over a period of 7 days. We assess food interaction in a 3-hr window, after providing a complex lab standard diet, to monitor HDF. Future studies would be needed to assess the effect of 14-day HSD on taste perception using the experimental design in this study (Figure 1A).The HDF response of HSD-fed flies (Figure 1C, days 3–10) is significantly lower than that of NF-fed flies, but they sense energy deficit and mobilize fat stores accordingly (Figure 1F and G). Hence, HSD-fed flies can calibrate their HDF to compensate only for the amount of fat lost in starvation. Nonetheless, this capacity of flies to couple energy sensing and feeding motivation is lost beyond day 14, as evidenced by the loss of HDF (Figure 1C, Figure 1—figure supplement 1A) and continuous TAG breakdown (Figure 1F and G). Strikingly, subjecting 14-day HSD-fed flies to prolonged starvation (up to 32 hr) was insufficient to induce increased HDF (Figure 1H). While there was an uptick in feeding behavior at 20 hr of starvation, this hunger response was not sustained at 24 and 32 hr (Figure 1H), even though flies continued to mobilize TAG reserves at 24 and 32 hr (Figure 1I and J). Thus, prolonged exposure to HSD leads to uncoupling nutrient sensing and feeding behavior.

Notably, fly and mammalian DIO models have striking differences and similarities. Mice show linear weight gain on obesogenic diets, but flies’ rigid exoskeleton limits their capacity to store TAG beyond a certain point (Han et al., 2020; Hatori et al., 2012; Lin et al., 2000; Figure 1—figure supplement 2). However, similar to mammals, prolonged exposure to HSD, strongly associated with phospholipid dysregulation (Sharma et al., 2013; Chang et al., 2019; Anjos et al., 2019), leads to reduced insulin sensitivity (Chang et al., 2019; Musselman et al., 2011). We show that the levels of Dilp5, the fly’s insulin ortholog, are reduced in the IPCs of HSD-fed flies (Figure 2A). However, we do not detect a decrease in Dilp5 or Dilp2 mRNA levels (Figure 2—figure supplement 1); this is suggestive of increased insulin secretion on HSD, similar to previously reported (Pasco and Léopold, 2012). Consistent with the idea that 14-day HSD triggers insulin resistance, we observe elevated FOXO nuclear localization in the fat bodies of the HSD-fed flies (Figure 2B), despite a likely increase in Dilp5 secretion on HSD (Figure 2A). Again, these findings align with mammalian studies showing that dysregulated FOXO signaling is implicated in insulin resistance, type 2 diabetes, and obesity (Gross et al., 2008).

HSD and fat-specific Pect-KD cause changes to the phospholipid profile

Changes in the lipidome are strongly correlated with insulin resistance and obesity (Mousa et al., 2019). However, less is known about how the lipidome affects feeding behavior. To this end, we analyzed the lipid profiles of NF and HSD-fed flies over time (Figure 3). As expected, exposure to HSD increased the overall content of neutral lipids compared to the NF flies, with TAGs and DAGs increasing the most, which is consistent with other DIO models (Musselman et al., 2011; May et al., 2019; Deshpande et al., 2014). Surprisingly, we noted that 14 days of HSD treatment caused a decrease in FFAs and a rise in TAGs and DAGs (Figure 3—figure supplement 1A). We speculate that this reduction in FFA may be due to their involvement in TAG biogenesis (Weiss et al., 1960). We were interested to see whether the decrease in FFA correlated to a particular lipid species as PE and PC are made from DAGs with specific fatty acid chains. However, further analysis of FFAs at the species level did not reveal any distinct patterns. Most FFA chains decreased in HSD, including 12.0, 16.0, 16.1, 18.0, 18.1, and 18.2 (Figure 3—figure supplement 1B). This data was more suggestive of a global decrease in FFA, likely converted to TAG and DAG rather than depleting a specific fatty acid chain.

On day 14 of HSD treatment, when HDF response begins to degrade (Figure 1C, Figure 1—figure supplement 1), PE and PC levels rise dramatically, whereas LPE significantly decreases. Interestingly, similar patterns of phospholipid changes have been associated with diabetes, obesity, and insulin resistance in clinical studies (Sharma et al., 2013; Chang et al., 2019; Anjos et al., 2019; Lim et al., 2011), yet no causative relationship has been established (Sharma et al., 2013; Chang et al., 2019; Anjos et al., 2019). Intriguingly, we find that PC balance appears dispensable for maintaining HDF-response. But both the mitochondrial and cytosolic PE pathways seem critical for HDF response (Figure 7). Multiple pathways synthesize PE. Studies have shown that in addition to the mitochondrial PISD (Steenbergen et al., 2005) and cytosolic CDP-ethanolamine Kennedy pathway (Calzada et al., 2016; Birner et al., 2001), PE can be synthesized from LPE (Riekhof and Voelker, 2006). This pathway is named the exogenous lysolipid metabolism (ELM) pathway. ELM can substitute for the loss of the PISD pathway in yeast and requires the activity of the enzyme lyso-PE acyltransferase (LPEAT) that converts LPE to PE (Riekhof et al., 2007). In this study, we noted PE levels were upregulated on HSD while LPE levels were downregulated (Figure 3).

In contrast, fat-specific Pect-KD caused PE levels to trend downward, whereas LPE was upregulated (Figure 6A). Though the level changes for PE and LPE are contrasting between 14-day HSD lipidome and Pect-KD, under both states, there is an imbalance of phospholipids classes PE and LPE. Hence, we propose maintaining the compositional balance of phospholipid classes PE and LPE is critical to HDF and insulin sensitivity.

The role of the minor phospholipid class LPE remains obscure. Our study observes that the LPE imbalance occurs during prolonged HSD exposure (Figure 3) and when fat body Pect activity is disrupted (Figure 6A). This suggests that LPE balance likely plays a role in insulin sensitivity and the regulation of feeding behavior. We anticipate that this observation will stimulate interest in studying this poorly understood minor phospholipid class. In future work, it would be interesting to test how the genetic interactions between the enzyme that converts LPE to PE, called LPEAT (Riekhof et al., 2007), and Pect manifest in HDF. Specifically, it will be interesting to ask whether reducing or increasing LPEAT will restore PE-LPE balance to improve the HDF response in HSD-fed flies and Pect-KD. Future studies should explore how LPE-PE balance can be manipulated to affect feeding behaviors.

In addition to changes in phospholipid classes (Figure 6—figure supplement 2C), we found that HSD caused an increase in the concentration of PE and PC species with double bonds (Figure 3—figure supplement 1C). Double bonds create kinks in the lipid bilayer, leading to increased lipid membrane fluidity, impacting vesicle budding, endocytosis, and molecular transport (Ben M’barek et al., 2017; Choudhary et al., 2018). Hence, a possible mechanism by which HSD induces changes to signaling by altering the membrane biophysical properties, such as by increased fluidity; this would impact various cellular processes, including synaptic firing and inter-organization vesicle transport. Consistent with this idea, we observe a significant reduction in the trafficking of ApoII-positive lipophorin particles from adipose tissue to the brain. Targeted experiments are required to understand how lipid membrane fluidity alters hunger response fully.

Pect activity in fat and its impact on fat–brain communication

To explore the idea that fat–brain communication may be perturbed under HSD and Pect knockdown, we chose to examine a fat-specific signal known to travel to the brain. ApoLpp chaperones PE-rich vehicles called lipophorins traffic lipids from fat to all peripheral tissues, including the brain (Palm et al., 2012). ApoII, the Apolpp fragment harboring the lipid-binding domain, has been shown to regulate systemic insulin signaling by acting on a subset of neurons in the brain (Brankatschk et al., 2014). We found that both HSD treatment and Pect knockdown reduced ApoII levels in the brain (Figure 4A and B). Given that ApoII acts as a ligand for lipophorin receptors in the brain, ApoII may be a direct regulator of feeding. Alternatively, it could ferry signaling molecules and PE/PC lipids. In the future, it would be important to explore whether lipoprotein trafficking from fat-to-brain directly impacts the hunger response.

Conclusion

We have uncovered a role for the phospholipid enzyme Pect as an important component in maintaining HDF. Future work should explore the precise mechanism of how Pect and the associated disruption in phospholipid homeostasis can impact adipose tissue signaling. In sum, this study lays the groundwork for further investigation into Pyct2/Pect as a potential therapeutic target for obesity and its associated comorbidities.

Methods

Animals used and rearing conditions

The following strains were used in this article: w1118, PISD-RNAi (Bloomington #67763), Pect-RNAi (Bloomington #67765), eas-RNAi (Bloomington #38528), Pcyt2-RNAi (Bloomington #67764), Lpp-Gal4 on X (P.Leopold/S. Eaton [Géminard et al., 2009]), Luciferase-RNAi (FlyBase ID: JF01355), and w;;UAS-Pect III (FlyBase ID:FBal0347227, generously donated by Clandinin lab), UAS-HA-Apolopp-myc (generously donated by S. Eaton) (Brankatschk and Eaton, 2010). Flies were housed in 25°C incubators. In all experiments, only adult male flies were used. Flies were sexed upon eclosion and place on normal diet, a standard diet containing 15 g yeast, 8.6 g soy flour, 63 g corn flour, 5 g agar, 5 g malt, 74 mL corn syrup per liter, for 7 days. Anesthesia using a CO2 bubbler was used for initial sexing, then never used for the remainder of the experiment. After 7 days, flies were either maintained on normal diet or moved to an HSD, composed of the same composition as normal diet but with an additional 300 g of sucrose per liter (30% increase) for the length specified in the figures (typically 7 or 14 days). For measurements of HDF, a portion of flies from each diet were placed on starvation media (0% sucrose/1% agar) for 16 hr prior to the experiment.

Immunostaining

Immunostaining of adult brains and fat bodies was performed as previously described (Brent and Rajan, 2020; Rajan et al., 2017). Tissues were dissected in ice-cold PBS. Brains were fixed overnight in 0.8% paraformaldehyde (PFA) in PBS at 4°C, and fat bodies were fixed in 4% formaldehyde in PBS at room temperature. Following fixation, tissues were washed five times in 0.5% BSA and 0.5% Triton X-100 in PBS (PAT). Tissues were pre-blocked in PAT + 5% NDS for 2 hr at room temperature, then incubated overnight with the primary antibody in block at 4°C. Following incubation, tissues were washed five times in PAT, re-blocked for 30 min, then incubated in secondary antibody in block for 4 hr at room temperature. Samples were washed five times in PAT, then mounted on slides in Slow fade gold antifade. Primary antibodies were as follows: chicken anti-Dilp2 (1:250; this study); rabbit anti-Dilp5 (1:500; this study); rabbit anti-ApoII (1:500; this study), rabbit anti-FOXO (1:500, gift from Leopold Pierre); and mouse-anti-lamin (1:100; ADL67.10 DSHB; RRID:AB_528336). Secondary antibodies from Jackson ImmunoResearch (1:500) include donkey anti-rabbit Alexa 647 (RRID:AB_2492288); donkey anti-rabbit Alexa 488 (RRID:AB_2313584); donkey anti-chicken Alexa 647 (RRID:AB_2340379); and donkey anti-rabbit Alexa 594 (RRID:AB_2340621). Lipid droplets were stained with lipidtox (1:500, Thermo Fisher Cat#H34477) overnight at room temperature. Images were captured with Zeiss LSM 800 confocal system and analyzed with ImageJ.

Image analysis

Quantification of the number of puncta and percentage area occupied by ApoII immunofluorescence was done using ImageJ. Maximum-intensity projections of z-stacks that spanned the entire depth of the IPCs at 0.3 um intervals were generated. A region of interest was manually drawn around the IPCs and a binary mask for the ApoII channel was created using automated Moments thresholding values, which was followed by watershed postprocessing to separate particles. The number of particles and the area fraction were measured using the ‘analyze particles’ function.

All images were acquired on the same day to minimize variability among samples. The fluorescent intensity of Dilp 5 was measured using z-stack summation projections that included the full depth of the IPCs. A region of interest around the IPCs was manually drawn and the integrated density values were acquired using ImageJ (Schneider et al., 2012). To measure nuclear FOXO accumulation, a similar number of confocal stacks were acquired for each tissue sample. For FOXO, image analysis was performed in the MATLAB R2020b environment, and the associated scripts are available at GitHub address. FOXO accumulation in Drosophila adult fat cells was assessed by measuring the mean voxel GFP intensity in the nucleus that is delimited by the lamin antibody signal. To generate the 3D nuclear masks, lamin stacks were first maximally projected along the z-axis, and after global thresholding, basic morphological operations, and watershed transforms, the locations of the nuclear centroids in the x-y plane were used to scan the z-stacks and reconstruct the nuclear volume. The accuracy of the segmentation was assessed by manual inspection of random cells. Once the nuclear compartment was reconstructed in 3D, it was used as a volumetric mask to extract intensity values of the FOXO reporter signal and compute the mean voxel intensity in the nucleus. Two-sided Wilcoxon rank-sum tests were performed to assess the statistical significance of pairwise comparisons between experimental conditions.

Lipidomics

Whole adult male flies were flash frozen in liquid nitrogen either after 7 or 14 days on normal diet or HSD. 10 flies were used per biological sample and 10 biological replicates were used for each diet and timepoint. For Pect manipulation lipidomics, LppGal4>UAS-Luc-RNAi, LppGal4>UAS-Luc, LppGal4>UAS-Pect-RNAi, and LppGal4>UAS-Pect flies were generated and flash frozen after 7 days on NF. Frozen samples were sent to the Northwest Metabolomics Research Center for targeted quantitative lipid profiling using the Sciex 5500 Lipidyzer (see Hanson et al., 2019 for detailed methods).

Feeding behavior

For HDF analysis, age-matched w1118 flies were given a normal diet or HSD for 5, 7, 14, 21, 24, and 28 days after an initial 7 days of development on a normal diet. All other experiments were performed for 7-day or 14-day durations. Then, 16 hr prior to feeding behavior assessment, half of the flies from each treatment were moved to starvation media 0%. During the 3-hr assessment window of feeding behavior, individual flies were placed in a single well of FLIC and supplied with a 5% sucrose liquid diet for all FLIC experiments. For feeding behavior involving Gal4>UAS manipulation, a 1% sucrose agar diet was substituted for the 0% sucrose agar 16 hr starvation to avoid fly death. Detailed methods for how FLIC operates can be found in Ro et al., 2014. Fly feeding was measured for the first 3 hr in the FLIC, and all FLICs were performed at 10 am local time. For each FLIC, half of the wells (n = 6/FLIC) contained the fed group, and the other half contained the starved group of flies for direct comparison. A total of 12–30 flies were measured for analysis of feeding. Any signal above 40 (a.u.) was considered a feeding event. Analysis of feeding events was performed using R.

Triglyceride measurement

Whole-body TAG measurements were performed in accordance with previously published methods (Rajan et al., 2017). In brief, whole flies (n = 3) were used per biological replicate with 8–9 replicates used for each timepoint and treatment. Flies were collected for TAG for all timepoints and treatments measured for feeding behavior (see above). Data was normalized to TAG levels per number of flies. Significance was calculated using two-way ANOVA.

Survival assay

Survival curves were performed using flies harvested in a 24-hr time frame and aged for 7 days, then subjected to either normal lab food or HSD. Ten males per vial were flipped onto 1% sucrose agar starvation food. The number of dead flies was recorded each day until every fly had died. Flies were kept in a 25°C incubator with a 12 hr light–dark cycle for the entirety of the experiment. Survival analysis was performed using the Survival Curve module of GraphPad Prism. A Mantel–Cox test was used to determine statistical significance. Greater than 90 flies were used per condition per curve.

Gene expression

Thirty fly fat bodies (for Pect) or heads (for Dilps) of each genotype were dissected in RNAlater. Immediately after dissection, fat bodies were moved to tubes of 200 µL RNAlater on ice. RNAlater was then removed, 30 µL of trireagent and a scoop of beads were added, and fat bodies were homogenized using a bullet blender. RNA was then isolated using a Direct-zol RNA microprep kit following the manufacturer’s instructions. Isolated RNA was synthesized into cDNA using the Bio-Rad iScript RT supermix for RT-qPCR and qPCR was performed using the Bio-Rad ssoAdvanced SYBR green master mix. Primers used in the article are as follows: Robl (endogenous control), forward: AGCGGTAGTGTCTGCCGTGT and reverse: CCAGCGTGGATTTGACCGGA; Pect, forward: CTGGAAAAGGCTAAGAAACTGGG and reverse: TCTTCAGTGACACAGTAGGGAG; alpha-tubulin (endogenous control), forward: ATCGAACTTGTGGTCCAGACG and reverse: GGTGCCTGGAGGTGATTTGG; Dilp2, forward: GCCTTGATGGACATGCTGA and reverse: CATAATCGAATAGGCCCAAGG; Dilp5, forward: GCTCCGAATCTCACCACATGAA and reverse: GGAAAAGGAACACGATTTGCG; Pect. Relative quantification of mRNA was performed using the comparative CT method and normalized to Robl mRNA expression. For each experiment, three biological replicates were used with three technical replicates used for qPCR.

Statistical methods

A t-test or ANOVA was performed using PRISM. Boxplots and standard deviation calculations were either performed through Prism or R. R packages used in this article included tidyverse (http://dx.doi.org/10.21105/joss.01686), ggplot2 (https://ggplot2.tidyverse.org), and ggthemes (https://github.com/jrnold/ggthemes, Arnold, 2022).

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures.

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Decision letter

  1. Tania Reis
    Reviewing Editor; University of Colorado Anschutz Medical Campus, United States
  2. David E James
    Senior Editor; The University of Sydney, Australia

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors' note: this paper was reviewed by Review Commons.]

Thank you for submitting "Fat Body Phospholipid State Dictates Hunger Driven Feeding Behavior" for consideration at eLife. Your article has been reviewed by the same 3 peer reviewers that initially reviewed your work at Review Commons, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor.

Comments to the Authors:

The reviewers were very positive and reassured by the lipidomics data clarifying the relationship between Pect levels, phospholipid levels, and HSD. However, the major concern remains: the manuscript does not have sufficient support for the model that hunger signals are indeed disrupted by Pect manipulations. An alternative hypothesis is still possible, that fatter flies have delayed hunger perception due to the extra levels of stored energy and, therefore, a delayed need for food, and would need to be starved longer in order to become hungry. For this reason, we are sorry to say that, after consultation with the reviewers, we have decided that at this time this work will not be considered for publication by eLife. However, due to the excitement about a potential molecular mechanism of hunger response, if the major concern can be addressed, we would be happy to reconsider this decision.

Specifically, one of the experimental suggestions from one of the reviewers is "to test a range of fasting times. Knowing that the authors' have affected 'hunger driven feeding' regardless of fasting time would be impressive. I would also suggest doing a simple starvation resistance experiment." If results show that indeed there is no difference in the hunger-driven response and that it's all due to differences in energy stores, we would not be as excited to reconsider the work. If, on the other hand, levels of energy stores are uncoupled from this response, we would be enthusiastic to revisit this work.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Fat Body Phospholipid State Dictates Hunger Driven Feeding Behavior" for further consideration by eLife. Your revised article has been evaluated by David James (Senior Editor) and a Reviewing Editor.

The manuscript has been greatly improved but there are some remaining minor issues that need to be addressed in the text, as outlined below:

1) The new starvation survival data is inconsistent with previous literature showing that higher sugar diets lead to fatter flies and increased starvation resistance. This could be due to differences in the experimental setup (survival on 1% sucrose/agar versus agar alone). This experiment is therefore not easy to interpret since it is not clear how much of the 1% sucrose the flies are consuming. We suggest that you remove Figure S1B and the corresponding text since the data should not be interpreted as showing that HSD flies are "starvation" sensitive, as they have access to 1% sucrose.

2) Note that for the hunger/feeding measurements after "starvation", the Methods state that sometimes flies were starved for 16 hr on "0% sucrose liquid diet" (is this just water?- please clarify), and sometimes they were "starved" for 16 hr on "1% sucrose". Please ensure these different approaches are clear when presenting the data and the data are interpreted in the right context (of full starvation (0% sucrose liquid diet) or low-calorie sugar diet (1% sucrose).

3) Please cite PMID: 31067455 and PMID: 32539934, AND discuss your data in the context of their findings on how high sugar diets affect sweet taste perception and satiation. While the manuscript is cited, we'd like to have you include in the discussion how their results (e.g. 7 days on HSD significantly increased feeding via the FLIC assay, the same technique used in this manuscript) fits with what you describe here. Specifically discuss, why you think you don't see this same increase in feeding with your chronic HSD?

4) The feeding assay used in this manuscript- FLIC assay- does not actually measure food intake. Rather, it measures how often the fly touches the food. PMID: 31067455 and PMID: 32539934 called them "licks" in their manuscript. Since it is well established from several labs (e.g., Dus, Neely) that chronic HSD decreases taste sensitivity to sugar. We suggest adding this caveat to the Discussion: "It's not clear how food interactions (and therefore measurements using the FLIC assay) are affected by sweet taste sensitivity, which is known to be altered by chronic HSD. Future studies might…"

https://doi.org/10.7554/eLife.80282.sa1

Author response

We are very grateful for this reviewer identifying this this methods description error and bring it to our attention. We used 0% sucrose agar for overnight starvation in this study as most labs do. The error occurred because we were using another manuscript from the lab to help draft the methods section (PMID: 29017032). In that study, where we assayed the effect of chronic starvation our lab used: “1% sucrose agar for 5 days at 25C”. However, in this current study, because we are testing acute effects of overnight starvation, we are using 0% sucrose agar.

Pect mRNA level is higher with HSD. This is surprising because not only, as authors mention, is increased PC32.2 with HSD suggests lower Pect activity, but also because Pect RNAi phenocopies long-term HSD in HDF behavior, lipid morphology, FOXO accumulation in fat body. The authors speculate that the data "likely shown an upregulation in an attempt to mediate the Pect dysregulation occurring at the protein level." If that were true, a western blot may be informative. Zhao and Wang (2020, PLoS Genetics) generated a Pect antibody that seems compatible with western blot applications. That being said, I don't think such data is critical for the manuscript. I mention this simply as a suggestion for the authors.

a. page 8, line 22-23, did you mean to write "Given how PC32.2 is elevated after 14 days of exposure to HSD, we assumed that Pect levels would be low for flies under HSD," not "high?" Otherwise the subsequent 2 sentences don't make sense.

We agree that the most confusing aspect of the study was that Pect mRNA levels being very high on Day 14 HSD, but nonetheless the effects of Pect-KD phenocopied HSD. To resolve this, we have now performed lipidomic analyses on whole adult flies, when Pect is knocked-down (KD) by RNAi in the fat tissue. We now present a new dataset in Figure 6.

Two striking changes occur. They are:

  1. Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3).

  2. Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding increase in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). In contrast, PE 36.2 trends upwards on 14 day HSD (Figure S7C) though not significantly.

On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

We agree that a western blot would be informative as well, but we were unable to obtain the reagent from Dr. Wang’s group, precluding us from performing this request.

To ensure that we appropriately discuss and clarify this issue, we have now included a section in the discussion – Page 14 Lines 26-34- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment.

“Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9), but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

Reviewer #1 (Significance (Required)):

The work is potentially novel and interesting, but at this stage it's difficult to interpret what the phenotype signifies. Although the manuscript could be revised simply by modifying the text, experimentally addressing the concerns would significantly improve the work.

In sum, we hope we have addressed the key concern for Reviewer #1 as to whether the behavior we report here is indeed a dampening of starvation-induced feeding, or an effect of increase in baseline feeding. We hope that by reviewing our non-normalized data, they can appreciate that it is the former. Also, we hope that Reviewer #1 appreciates that we have strived to address the concerns by additional experiments, to clarify our findings and improve the impact of the work.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

This intriguing manuscript by Kelly and colleagues uses the fruit fly Drosophila melanogaster as a model to understand how diet-induced obesity alters the feeding response over time. In particular, the authors findings indicate that chronic exposure to a high-sugar diet significantly alters the starvation-induced feeding response. These behavioral studies are complemented by a lipidomics approach that reveals how a chronic high sugar affects many lipid species, including phospholipids. The authors then pursue mechanistic studies that indicate phospholipid metabolism within the fat body appears to remotely affect insulin secretion from the insulin producing cells. Moreover, the changes in phospholipid abundance are associated with changes in insulin-signaling, including increased insulin secretion from the IPCs and elevated levels of FOXO within the nucleus.

I find the study to be potentially very important – the authors combine a longitudinal study that would be difficult in any other model with the powerful genetic tools available in the fly. The conclusions are mostly convincing, but a few follow-up experiments are required:

We are grateful for the reviewers constructive, detail-oriented, and balanced feedback, and their recognition of the value of this study. Now, we have performed additional experiments to address the key concerns raised by all reviewers. We hope that on reading the revised version of our study, that the reviewer continues to feel positive about the message of this study and its potential impact.

1. The key conclusions from the manuscript assume that manipulation of Pect expression levels alters phosphatidylethanolamine (PE) levels. However, the authors make no attempt to verify that the genetic experiments described herein actually affect PE levels. At a minimum, changes in PE levels should be verified for the Pect knockdown and overexpression lines. Similarly, there is no evidence that manipulation of either EAS or Pcyt2 induces the expected metabolic effects. I'm not asking that the longitudinal feeding experiments be repeated, simply that the authors measure the relevant lipid species, preferably with a targeted LC-MS approach.

Prompted by this reviewer, we performed targeted LC-MS on whole adult flies, on normal diet, to assess lipid levels for fat-specific Pect-KD and overexpression. We decided to focus on Pect, as its knock-down even on normal diet causes a dampened hunger-driven feeding behavior (Figure 7A) and phenocopied a 14-day HSD feeding phenotype.

We now present a new dataset in Figure 6. Two striking changes occur:

They are:

i) Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding decrease in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). It is to be noted that though overall levels of all PE species trend downwards, like the Clandinin lab study on Pect (PMID: 30737130), we did not find a significant change in the overall PC and PE levels.

ii) Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3).

On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

Finally, fat-specific Pect-OE did not cause significant changes to lipid species (Figure S9). This could either be due to the fact that in fat-specific Pect-OE flies under normal food and that we were assaying whole body lipid levels and not fat-specific lipid changes. But to counter that, even a 60% reduction in Pect mRNA levels (Figure S6A), was sufficient to produce an effect on whole body phospholipid balance (Figure 6). Hence, we speculate that by maintaining a basally higher (7-fold higher Pect mRNA level Figure S6A), might allow 14-day HSD-fed flies to buffer the negative effects of HSD and we predict that it might take longer to disrupt the phospholipid balance and HDF response.

We have now included a section in the discussion – Page 14 Lines 26-34- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment.

“Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9), but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

  • A central hypothesis in the study is that the HSD over a period of 14 days results in insulin resistant and that these changes are leading to changes in hunger dependent feeding. I would encourage the authors to determine if Foxo mutants are resistant to these HSD-induced effects on HFD.

We thank the reviewers for this suggestion. However, given that dFOXO nuclear localization rather than expression levels regulate insulin sensitivity, we feel that disrupting dFOXO levels via mutation or knockdown will produce a plethora of indirect effects including developmental abnormalities (PMID: 24778227, PMID: 16179433, PMID: 29180716, PMID: 12893776). Our data suggest that chronic HSD treatment and Pect affect insulin sensitivity in fat tissue. However, we feel that investigating whether insulin sensitivity/FOXO signaling in fat tissue regulates feeding behavior is outside the scope of our work.

  • In lines 25-30, the authors draw the conclusion that an increase in unsaturated fatty acid species is associated with the HSD and that these changes results in a more fluid lipid environment. While I agree with the model, the manuscript contains no evidence to support such a model. Either test the hypothesis or move the last line of the section to the discussion.

We thank the reviewer for this important and insightful comment. We agree that the data we presented and discussed in the original version is at the moment speculative. Addressing the hypothesis that increase in unsaturated fatty acid species result in a more fluid lipid environment will require us to build tools and expertise. Hence, this hypothesis is better suited for exploration in a future study. Given this, we have moved this out of the Results section into the Discussion section titled “HSD and fat-specific PECT-KD causes changes to phospholipid profile” (See excerpt below from page 13, lines 24-35).

“In addition to changes in phospholipid classes, we found that HSD caused an increase in the concentration of PE and PC species with double bonds (Figure S4C and S4D). Double bonds create kinks in the lipid bilayer, leading to increased lipid membrane fluidity which impacts vesicle budding, endocytosis, and molecular transport14,92. Hence it is possible that a mechanism by which HSD induces changes to signaling is by altering the membrane biophysical properties, such as by increased fluidity, which would have a significant impact on numerous biological processes including synaptic firing and inter-organ vesicle transport.”

Also, as per the reviewer’s guidance, given that we are speculating here, we have also shifted this dataset from Main figure 4 to supplement S4C and S4D.

In addition, lines 25-30 state that FFAs are increased after 14 days of a HSD. Figure 3A shows the exact opposite – FFAs are significantly decreased in 14 day fed animals despite being elevated in the 7 day fed animals. This is an interesting result that warrants discussion. Moreover, I would encourage to examine the lipidomic data more carefully to ensure that the text accurately portrays the lipid profiles.

We apologize for misstating that FFAs are decreased on 14-day HSD in the lines 25-30. It was an error and we have corrected this. We agree with the reviewer that the reduction of FFA on Day 14-HSD is an intriguing and unexpected observation that needs to be emphasized and further discussed. To this end, we have added figure S4B, wherein we have provided the difference in FFA concentration (by species) after days 7 and 14.

Furthermore, we have discussed what the potential meaning of reduced FFA at Day 14 implies in page 12, lines 19-27 of the Discussion section titled “HSD and fat-specific PECT-KD causes changes to phospholipid profile”. We have stated the following-

“We speculate that this reduction in FFA maybe due to their involvement in TAG biogenesis (PMID: 13843753). We were interested to see if the decrease in FFA correlated to a particular lipid species, as PE and PC are made from DAGs with specific fatty acid chains. However, further analysis of FFAs at the species level did not reveal any distinct patterns. The majority of FFA chains decreased in HSD, including 12.0, 16.0, 16.1, 18.0, 18.1, and 18.2 (Figure S4B). This data was more suggestive of a global decrease in FFA, likely being converted to TAG and DAG, rather than a specific fatty acid chain being depleted.”

The processed lipidomics data should also be included as supplementary data table so that they can be independently analyzed by the reader.

We thank the reviewer for this suggestion. As per the reviewers request, we have included the raw data as an attachment in our supplementary material (Supplementary Files 1-3.), so that interested readers can use the datasets generated in this study for future work and further analysis.

Page 3, Line 1 and 2: "…have been shown to impact feeding behavior and metabolism that leads to…" This is an awkward and grammatically incorrect sentence.

Page 3, Lines 7-32 is one very large paragraph but contains concepts that should be broken down over at least three paragraphs.

Page 3, Line 25: A description of the reaction catalyzed by Pect would be helpful for a manuscript focused on Pecte activity.

Page 4, Line 10: "previously characterized method of eliciting diet induced feeding behavior." As stated in the text, the method is previously described yet the manuscript characterizing the method isn't cited.

Figure legend 3 contains a random assortment of capitalized lipid species. Also, the names of lipid species are inappropriately broken into multiple names. Please use correct nomenclature throughout the manuscript.

The list above is nowhere near comprehensive. The manuscript requires significant editing.

We are grateful to the reviewer for drawing our attention to these errors. We have made significant edits to the revised manuscript to address the above-mentioned concerns, as well as made additional textual changes throughout and copyedited it. We hope that the reviewer will find the manuscript reads better and the clarity and preciseness is significantly improved.

Reviewer #2 (Significance (Required)):

I find the study to be potentially very important – the authors combine a longitudinal study that would be difficult in any other model with the powerful genetic tools available in the fly. The findings will significantly advance our understanding of how lipid metabolism links dietary nutrition with feeding behavior.

Once again, we are grateful for this reviewer’s thoughtful critique and encouraging words regarding our work and its potential impact.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary:

This manuscript uses Drosophila to investigate how diet-induced obesity and the changes in the lipid metabolism of the fat boy modulate hunger-driven feeding (HDF) response. The authors first demonstrate that chronic exposure (14 days) of high sugar diet (HSD) suppresses HDF response. Through lipidome analysis, the authors identify a specific class of lipids to be elevated upon chronic HSD feeding. This coincided with the changes in expression of Pect, an enzyme that regulates the biosynthesis of these lipids. Modulating the expression of Pect specifically in the fat body affected HDF response.

We thank this reviewer for their rigorous and thoughtful critique and for identifying a key issue with our original study pertaining to a gap in how Pect mRNA levels on 14-day HSD are elevated but the Pect-KD phenocopies the HDF. Now by performing whole-body adult fly lipidomic on fat-specific Pect-KD we have resolved this issue and provided clarity on role of Pect in maintaining phospholipid homeostasis and thus subsequently impacts hunger-driven feeding. We hope the reviewer finds that the revised manuscript provides further clarity to the functional link between Pect’s role in fat-body and hunger-driven feeding.

Major comments:

The author claim that the HDF response in HSD is distinct between early (5d, 7d) and chronic (day 14) HSD feeding. However, the data seem to indicate that HDF response is significantly decreased at all time points in HSD. For example, at day 5 HDF response was increased only 3fold in HSD (Figure 1C) compared to around 50-fold increase in NF (Figure 1B). The scale of the Y-axis in Figure 1B and 1C is an order of magnitude different. Including the starved data (NFstv and HSDstv) in Figure S1, normalized to NF fed group, would better visualize the overall trends. Related to this, having the source data for the actual number of feeding events would be useful (e.g., to see the baseline changes in feeding in different time points in Figure 1 and the effect of genetic manipulations in Figure 7).

As per the reviewers request, we now have modified our graphs to show source data (Figure S1) and show the raw feeding events.

Then in the non-normalized graphs we plot, over a longitudinal time course, baseline and hunger-driven feeding events (Figure 1B-D). We also show that HSD fed flies do not display increased baseline feeding (Figure 1D) suggesting that the effect we see on HDF are no clouded by increased baseline feeding.

Yes, the reviewer makes an important point that HDF response on HSD fed flies is of a lower magnitude than NF fed flies. We think that is a biologically meaningful observation, as it suggests that flies have a remarkably fine-tuned ability to coordinate food-intake with nutrient store levels.

Now we have included a paragraph in the Discussion, Page 11 Lines 23-27, that say the following to ensure the readers appreciate this salient point raised by this reviewer.

It is to be noted that the HDF response of HSD-fed flies (Figure 1C, Days 3-10) is of lower order of magnitude than the NF-fed flies. This suggests that in addition to sensing an energy deficit and mobilizing fat stores (Figure 1F, 1G, S1), HSD fed flies calibrate their starvation-induced feeding to compensate only for the lost amount of fat. Overall, this suggests that flies have a remarkably finetuned ability to coordinate food-intake with nutrient store levels.

The association between fat body Pect level and phospholipid levels is not clear. Day 14 of HSD feeding shows high expression of Pect in the fat body and elevated levels of PC32.0 and PC32.2. The authors assume the high expression of Pect in the fat body is due to the compensatory response, but there are no data indicating downregulation of Pect levels at the earlier time points of HSD feeding. A previous study demonstrated that Pect mutant flies have lower levels of PC32.0 but higher PC32.2 (PMID: 30737130).

We agree that one puzzling aspect of the original version of this study was that Pect mRNA levels being very high on Day 14 HSD, but nonetheless the effects of Pect-KD phenocopied HSD. To resolve this, prompted by Reviewer #2 and #3 concerns, for this revised version we have now performed lipidomic analyses on whole adult flies, when Pect is knocked down (KD) by RNAi in the fat tissue. We now present a new dataset in Figure 6. Two striking changes occu. They are:

  1. Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3).

  2. Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding increase in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). In contrast, PE 36.2 trends upwards on 14 day HSD (Figure S7C) though not significantly.

On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

On day 14, HDF response was increased 70-fold in w1118 flies in NF (Figure 1B; w1118), but only 2.5-fold in lpp>LucRNAi control flies in NF (Figure 7A). This suggests that lpp-gal4 driver lines have a significant effect on HDF response. Using a different fat-body specific Gal4 line would be necessary to validate conclusions.

Regards reduced HDF magnitude, in our experience using UAS-Gal4 reduces HDF response magnitude consistently and cannot be compared to w1118 which is more robust. To account for background differences, we use Uas-Gal4 with control RNAi. It clearly shows differences in HDF response on starvation, but Pect and Pisd RNAi does not (Figure 7A). Hence, given that this experiment internally controls for any changes in HDF response for UAS-Gal4>RNAi, we conclude that HDF response in disrupted in Pect and PISD KD (Figure 7).

We only presented the Lpp-driver in our study, as this driver is the only fat-specific driver that has no leaky expression in other tissues, and is specific to fat as apolpp promoter used to generate this Gal4 line is only expressed in fat tissue (Eaton and colleagues, PMID: 22844248). Other widely used fat-specific drivers, including the pumpless-Gal4 (ppl-Gal4) driver has leaky expression in gut or other tissues (See Table 2 of this detailed study by Dr. Drummond- Barbosa https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642949/). If the reviewer is aware of a fat-specific Gal4 line, other than Lpp-Gal4, which has a highly specific expression in the fat tissue without leaky expression in other tissues, then we are happy to take onboard the reviewer’s suggestion and try that fat-specific Gal4 that they suggest.

HSD feeding promotes Pect expression (Figure S3C) and global changes in phospholipid levels (Figure 3, 4). Therefore, shouldn't Pect overexpression (not Pect RNAi) in a normal diet mimic HSD feeding state and promote loss of HDF response? Conversely shouldn't knockdown of Pect in HSD rescue loss of HDF response?

We agree that a puzzling aspect is that Pect mRNA levels are significantly elevated in HSD Day-14, but Pect-KD showed displays the inappropriate HDF response. As we have described in our response to this reviewer on Page 19, we believe that Pect-KD and HSD disrupt PE and LPE balance overall but in different ways. Whereas Pect-OE using cDNA expression in fat body does not cause a significant change to any lipid class (Figure S9), and our results suggest that basally higher level of PECT is likely to be protective on HSD with respect to HDF (Figure 7B).

To ensure that we appropriately discuss and clarify this issue, we have now included a section in the discussion – Page 14 Lines 26-33- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment. 5 “Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9), but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

We would have liked to test Pect protein expression on HSD, but since we were unable to access antibodies for Pect published in a prior study (PMID: 33064773) from Dr. Wang’s lab (see Page 10-11, of response to Reviewer #1). Hence, we were unable to test how the proteins levels of Pect correlate with the 250-fold increase mRNA expression.

In conclusion, we hope the reviewer appreciates that our results regarding Pect function are consistent with the main conclusion that achieving the right phospholipid balance between PE and LPE, is critical for an organism to display an appropriate HDF response.

Minor comments:

All graphs should plot individual data points and showed as box and whisker plot as much as possible.

Thanks for this suggestion, we have added individual data points to the vast majority of figures in the paper. We have made exceptions to graphs such as seen in figure 1 and FigureS4B-D where we find individual data points add an unnecessary layer of complexity. We hope these changes provide additional clarity and strength to the claims made in this manuscript.

Data for day 14 missing in Figure S4A and S4B.

We have provided Day 14 for the PC composition and PE composition, due to changes in Figures, they are now S7A and S7B.

Reviewer #3 (Significance (Required)):

The interactions between diet-induced obesity, peripheral tissue homeostasis and feeding behavior is an interesting topic that can be addressed using Drosophila. This manuscript demonstrates how fat body Pect levels affect HSD induced changes in hunger-driven feeding response. However, at this point, the functional association between fat body Pect level, global phospholipid level, and loss of hunger-driven feeding response in chronic HSD feeding is not clear.

We hope the revised data, and discussion of the paper, provides well-substantiated functional association on the importance of maintaining phospholipid balance, driven by Pect enzyme, as a critical regulator of hunger-driven feeding behavior. As stated in the revised discussion, the key take home message of our manuscript is that on prolonged HSD exposure PC, PE and LPE levels are dysregulated, the loss of phospholipid homeostasis coincided with a loss of hunger driven feeding. Following this lead on phospholipid imbalance, we then uncovered a critical requirement for the activity of the rate-limiting PE enzyme PECT within the fat tissue in controlling hunger-driven feeding.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Comments to the Authors:

The reviewers were very positive and reassured by the lipidomics data clarifying the relationship between Pect levels, phospholipid levels, and HSD. However, the major concern remains: the manuscript does not have sufficient support for the model that hunger signals are indeed disrupted by Pect manipulations. An alternative hypothesis is still possible, that fatter flies have delayed hunger perception due to the extra levels of stored energy and, therefore, a delayed need for food, and would need to be starved longer in order to become hungry. For this reason, we are sorry to say that, after consultation with the reviewers, we have decided that at this time this work will not be considered for publication by eLife. However, due to the excitement about a potential molecular mechanism of hunger response, if the major concern can be addressed, we would be happy to reconsider this decision.

Specifically, one of the experimental suggestions from one of the reviewers is "to test a range of fasting times. Knowing that the authors' have affected 'hunger driven feeding' regardless of fasting time would be impressive. I would also suggest doing a simple starvation resistance experiment." If results show that indeed there is no difference in the hunger-driven response and that it's all due to differences in energy stores, we would not be as excited to reconsider the work. If, on the other hand, levels of energy stores are uncoupled from this response, we would be enthusiastic to revisit this work.

We thank you for reviewing our manuscript #13-05-2022-RA-RC-eLife-80282, titled "Fat Body Phospholipid State Dictates Hunger Driven Feeding Behavior". We much appreciate your time and efforts in consulting with the peer-reviewers and providing us with thoughtful comments on our submitted work.

We were pleased to note that the reviewers were reassured about the lipidomic datasets we presented in the revision. We noted that one unresolved issue in our interpretation of the hunger-driven feeding motivation of 14-day HSD-fed flies precluded the acceptance of our manuscript.

To recap, we had shown that by 16 hours of starvation, age-matched Normal Fed (NF) controls to display a strong hunger-driven feeding (HDF) response. But, the 14-day high sugar diet (HSD) fed flies do not. Figure S1. We interpreted this dataset to mean that prolonged 14-day exposure to HSD altered the hunger perception of flies on starvation.

However, the reviewers raised an alternative hypothesis: " fatter flies have delayed hunger perception due to the extra levels of stored energy and, therefore, a delayed need for food, and would need to be starved longer to become hungry".

To resolve this, the reviewer suggested two specific experiments.

  1. "to test a range of fasting times. Knowing that the authors' have affected 'hunger driven feeding' regardless of fasting time would be impressive."

  2. "I would also suggest doing a simple starvation resistance experiment."

We have now performed these experiments and present our results below.

  1. 14-day HSD-fed flies were subject to HSD, then starved for 16, 20,24, and 32 hours*. We assayed the hungerdriven feeding of all the starvation time points against the baseline 14-day HSD-fed in the same FLIC run (Author response image 1A). We observed that at 20 hours after starvation, flies display a short burst of feeding activity (Author response image 1A). However, by 24 hours and 32 hours, they do not show increased feeding activity (Author response image 1A). At 24 and 32 hours of starvation, these flies broke down 50% of their fat stores, which is statistically significant (Author response image 1B, 1C). NF-fed flies break down 50% of their fat stores by the 16hour time point, sufficient for them to display hunger-driven feeding (See Figure 1 of our manuscript). Hence, even though 14-day HSD-fed flies use up a significant portion of their energy stores at 24-32 hours, they do not display hunger-driven feeding. A linear regression analysis between feeding events and TAG levels suggests that TAG store levels and feeding events do not show any significant correlation (Author response image 1D). Hence, subjecting flies to a 14-day HSD disrupts their hunger-driven feeding regardless of fasting time and TAG stores.

* We find that beyond 32hrs starvation on a 0% sucrose diet, the flies die, so this is the furthest we can technically run this starvation response curve.

Author response image 1
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(A) Feeding events of 14-day HSD-fed flies at various starvation times. (B) TAG stores of 14-day HSD-fed flies at various starvation times. (C) Normalized TAG of 14-day HSD-fed flies at various starvation times. (D) Regression analysis of feeding events and TAG.

  1. We performed a starvation survival curve (on 1% sucrose agar) on flies fed 14-day HSD and compared them to age-matched controls kept on 14-day NF. 14-day HSD-fed flies were significantly less resilient to starvation than NF-fed flies (Author response image 2). Again, this is in keeping with the disrupted hunger response of the HSD-starved flies. Note 70-100 flies were used for this experiment.

Author response image 2
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Starvation survival on 1% sucrose agar of 14-day NF vs. HSD fed flies.

We were puzzled by your note that "the manuscript does not have sufficient support for the model that hunger signals are indeed disrupted by Pect manipulations". Thus, we would like to draw your attention again to the results we presented in the manuscript on the role of PECT in hunger-driven feeding (Figure 7A). Please note that fatspecific knockdown of PECT in flies fed a "normal" diet is sufficient to reduce HDF (Figure 7A) significantly. Despite showing a disrupted hunger response (Figure 7A), we noted that PECT-KD does not cause a significant change in TAG stores on a normal diet (Author response image 3). Hence, PECT-KD in fat disrupts hunger response in flies on normal lab diets without impacting energy store levels.

Author response image 3
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PECT-KD in fat tissue on normal diets does not alter TAG stores.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

The manuscript has been greatly improved but there are some remaining minor issues that need to be addressed in the text, as outlined below:

1) The new starvation survival data is inconsistent with previous literature showing that higher sugar diets lead to fatter flies and increased starvation resistance. This could be due to differences in the experimental setup (survival on 1% sucrose/agar versus agar alone). This experiment is therefore not easy to interpret since it is not clear how much of the 1% sucrose the flies are consuming. We suggest that you remove Figure S1B and the corresponding text since the data should not be interpreted as showing that HSD flies are "starvation" sensitive, as they have access to 1% sucrose.

We note your concern on the 0% vs 1% sucrose diets. 1. In standard lab conditions, flies live only a short 32-36 hours on 0% sucrose diets. In our experience, evaluating these short 0% starvation curves are unreliable. Hence, we and others have used 1% sucrose diets to analyze starvation response curves (PMID: 29017032; 23021220), since they allow flies to live for up to 15 days. Since the original email did not specify that these curves must be performed on non-standard 0% diet. we performed what is standard in the field for starvation curves i.e., 1% sucrose diet. Again, we feel that inclusion of this data is important, and is in response to a reviewer request. But given your reservations, we have removed the figure 1- supplement 1B and references to it in results and discussion. We note that this change has no significant impact on the conclusions of our study.

2) Note that for the hunger/feeding measurements after "starvation", the Methods state that sometimes flies were starved for 16 hr on "0% sucrose liquid diet" (is this just water?- please clarify), and sometimes they were "starved" for 16 hr on "1% sucrose". Please ensure these different approaches are clear when presenting the data and the data are interpreted in the right context (of full starvation (0% sucrose liquid diet) or low-calorie sugar diet (1% sucrose).

We have now included a more detailed methods section, as follows to describe the starvation conditions.

For hunger-driven feeding analysis, age-matched w1118 flies were given a normal diet or HSD for 5, 7, 14, 21, 24, and 28 days after an initial 7 days of development on a normal diet. All other experiments were performed for 7-day or 14-day durations. 16 hours prior to feeding behavior assessment, half of the flies from each treatment were moved to starvation media 0%. During the three hour assessment window of feeding behavior, Individual flies were placed in a single well of fly liquid-food interaction counter (FLIC) and supplied with a 5% sucrose liquid diet for all FLIC experiments. For feeding behavior involving Gal4>UAS manipulation, a 1% sucrose agar diet was substituted for the 0% sucrose agar 16 hours starvation to avoid fly death. Detailed methods for how FLIC operates can be found in Ro et al., 201447. Fly feeding was measured for the first three hours in the FLIC and all FLICs were performed at 10 am local time. For each FLIC, half of the wells (n=6/FLIC) contained the fed group, and the other half contained the starved group of flies for direct comparison. 12-30 flies were measured for analysis of feeding. Any signal above 40 (a.u.) was considered a feeding event. Analysis of feeding events was performed using R.

We note that only for datasets in figure 7, given that 0% sucrose agar diet caused lethality, we used the 1% sucrose agar diet. We have clearly indicated this – 1% sucrose diet- in the legends and Results section Page 8, lines 16-18.

“Note that for the starvation experiments in these UAS/Gal4 conditions, we observed lethality on a 0% sucrose diet. Hence, we used a low-nutrient diet (1% sucrose agar) to induce nutrient deprivation (See Methods).”

Also, in the revised version we specify that in the FLIC counter we use 5% sucrose liquid food during the feeding assessment for all experiments.

3) Please cite PMID: 31067455 and PMID: 32539934, AND discuss your data in the context of their findings on how high sugar diets affect sweet taste perception and satiation. While the manuscript is cited, we'd like to have you include in the discussion how their results (e.g. 7 days on HSD significantly increased feeding via the FLIC assay, the same technique used in this manuscript) fits with what you describe here. Specifically discuss, why you think you don't see this same increase in feeding with your chronic HSD?

The studies by Dus and colleagues evaluated food interactions in a 5-30% sucrose liquid diet over a 24-hour window for 7 days using FLIC. In our studies, we maintain flies on a standard lab (solid diet- which is more complex with proteins), or on 30% HSD (that is the addition of additional sucrose to the standard lab diet). We then evaluate their feeding interactions for 3 -hours only, after they have been starved or baseline. In Figure 1D, we presented results showing that under our conditions, 3-hour FLIC window, we did not observe a statistical significant change in baseline feeding behavior of NF vs. HSD fed flies within the 3-hour window. Nonetheless, our results don’t directly contradict the Dus et al. studies, given they are using a liquid sugar-based diet over a period of 7 days to measure feeding interactions. We have now discussed this as follows, in page 10 Line 15-19.

Under our experimental conditions, we find basal feeding to be statistically similar between NF fed and HSD fed conditions at all timepoints with exception of day 10 (Figure 1D). Note that Dus and colleagues reported that on a 20% sucrose liquid diet for 7-days elevated food interactions44, 85. However, the Dus et al. studies are not comparable with our study due to the large differences in experimental protocol. They evaluated taste preference changes and feeding interactions on 5-30% sucrose liquid diet in 24-hour window over a period of 7 days. We assess food interaction in a 3-hour window, after providing a complex lab standard diet, to monitor hunger-driven feeding.

4) The feeding assay used in this manuscript- FLIC assay- does not actually measure food intake. Rather, it measures how often the fly touches the food. PMID: 31067455 and PMID: 32539934 called them "licks" in their manuscript. Since it is well established from several labs (e.g., Dus, Neely) that chronic HSD decreases taste sensitivity to sugar. We suggest adding this caveat to the Discussion: "It's not clear how food interactions (and therefore measurements using the FLIC assay) are affected by sweet taste sensitivity, which is known to be altered by chronic HSD. Future studies might…"

As noted in response to #3 above, we have discussed the two studies and provided information to the readers that the experimental design of our work does not directly evaluate the taste sensitivity to sugar.

We note now that in the Discussion section in page 10 line 20 that:

Future studies would be needed to assess the effect of 14 day HSD on taste perception using the experimental design in this study (Figure 1A).

https://doi.org/10.7554/eLife.80282.sa2

Article and author information

Author details

  1. Kevin P Kelly

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Formal analysis, Investigation, Visualization, Methodology, Writing – original draft
    Contributed equally with
    Mroj Alassaf
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8632-2339

  2. Mroj Alassaf

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Data curation, Formal analysis, Writing – original draft, Writing – review and editing
    Contributed equally with
    Kevin P Kelly
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6277-9417

  3. Camille E Sullivan

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Data curation, Formal analysis, Investigation
    Competing interests
    No competing interests declared

  4. Ava E Brent

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Data curation, Formal analysis, Investigation
    Competing interests
    No competing interests declared

  5. Zachary H Goldberg

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Data curation, Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2972-9682

  6. Michelle E Poling

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  7. Julien Dubrulle

    Cellular Imaging Core, Shared Resources, Fred Hutch, Seattle, United States
    Contribution
    Visualization
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4186-7749

  8. Akhila Rajan

    Basic Sciences Division, Fred Hutch, Seattle, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing – review and editing
    For correspondence
    akhila@fredhutch.org
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1160-5796

Funding

National Institute of General Medical Sciences (GM124593)

  • Akhila Rajan

Directorate for Biological Sciences (2109398)

  • Kevin P Kelly

NIH Chromosome Metabolism and Cancer Training Grant (T32CA009657)

  • Kevin P Kelly

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Dr. Pierre Leopold for generously donating the FOXO antibody used in this article. We are grateful to Dr. Thomas Clandinin for gifting the UAS-PECT transgenic flies and the late Dr. Susan Eaton for the generous gift of the Lpp-Gal4 flies. We would also like to thank the Northwest Metabolomics Research Center team for their support in lipidomic profiling. This work was possible due to grants awarded to AR from NIGMS (GM124593) and New Development funds from Fred Hutch Cancer Center. KPK was supported by the NIH Chromosome Metabolism and Cancer Training Grant (T32CA009657) and is currently supported by the NSF Post-Doctoral Research Fellowship (NSF Award #2109398). Genomic reagents from the DGRC funded by NIH grant 2P40D010949 were used in this study. Stocks obtained from the Bloomington Drosophila Stock Center (NIH P40OD018537) and Transgenic RNAi Resource Project (NIGMS R01 GM084947 and NIGMS P41 GM132087) were used in this study. We are immensely grateful to the three anonymous peer reviewers for their incisive, constructive, and balanced feedback that significantly contributed to improving the clarity of this study.

Senior Editor

  1. David E James, The University of Sydney, Australia

Reviewing Editor

  1. Tania Reis, University of Colorado Anschutz Medical Campus, United States

Version history

  1. Preprint posted: December 17, 2021 (view preprint)
  2. Received: May 15, 2022
  3. Accepted: October 5, 2022
  4. Accepted Manuscript published: October 6, 2022 (version 1)
  5. Version of Record published: October 14, 2022 (version 2)

Copyright

© 2022, Kelly, Alassaf et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Kevin P Kelly
  2. Mroj Alassaf
  3. Camille E Sullivan
  4. Ava E Brent
  5. Zachary H Goldberg
  6. Michelle E Poling
  7. Julien Dubrulle
  8. Akhila Rajan
(2022)
Fat body phospholipid state dictates hunger-driven feeding behavior
eLife 11:e80282.
https://doi.org/10.7554/eLife.80282

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