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Starvation-induced regulation of carbohydrate transport at the blood–brain barrier is TGF-β-signaling dependent

  1. Helen Hertenstein
  2. Ellen McMullen
  3. Astrid Weiler
  4. Anne Volkenhoff
  5. Holger M Becker
  6. Stefanie Schirmeier  Is a corresponding author
  1. Department of Biology, Institute of Zoology, Technische Universität Dresden, Germany
  2. Institut für Neuro- und Verhaltensbiologie, WWU Münster, Germany
  3. Division of General Zoology, Department of Biology, University of Kaiserslautern, Germany
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Cite this article as: eLife 2021;10:e62503 doi: 10.7554/eLife.62503

Abstract

During hunger or malnutrition, animals prioritize alimentation of the brain over other organs to ensure its function and, thus, their survival. This protection, also-called brain sparing, is described from Drosophila to humans. However, little is known about the molecular mechanisms adapting carbohydrate transport. Here, we used Drosophila genetics to unravel the mechanisms operating at the blood–brain barrier (BBB) under nutrient restriction. During starvation, expression of the carbohydrate transporter Tret1-1 is increased to provide more efficient carbohydrate uptake. Two mechanisms are responsible for this increase. Similar to the regulation of mammalian GLUT4, Rab-dependent intracellular shuttling is needed for Tret1-1 integration into the plasma membrane; even though Tret1-1 regulation is independent of insulin signaling. In addition, starvation induces transcriptional upregulation that is controlled by TGF-β signaling. Considering TGF-β-dependent regulation of the glucose transporter GLUT1 in murine chondrocytes, our study reveals an evolutionarily conserved regulatory paradigm adapting the expression of sugar transporters at the BBB.

Introduction

A functional nervous system is essential for an animal’s survival. To properly function, the nervous system needs a disproportionately large amount of energy relative to its size. The human brain for example accounts for only about 2% of the body’s weight but uses around 20% of the resting oxygen consumption (Laughlin et al., 1998). Likewise, the insect retina consumes approximately 10% of the total ATP generated (Harris et al., 2012; Laughlin et al., 1998; Mink et al., 1981).

The nervous system is very susceptible to changing extracellular solute concentrations and thus needs to be separated from circulation. This task is performed by the blood–brain barrier (BBB), which prevents paracellular diffusion, and thereby uncontrolled influx of ions, metabolites, xenobiotics, pathogens, and other blood-derived potentially harmful substances. Protein, ion, and metabolite concentrations fluctuate to a much greater extent in circulation than in the cerebrospinal fluid, the brains extracellular milieu (Begley, 2006). Thus, fluxes over the BBB must be tightly regulated and only small lipid-soluble molecules and gases like O2 and CO2 can diffuse freely (van de Waterbeemd et al., 1998).

The enormous energy demand of the nervous system is mainly met by carbohydrate metabolism. The human brain takes up approximately 90 g glucose per day during adulthood and up to 150 g per day during development (Kuzawa et al., 2014). Since glucose and other carbohydrates are hydrophilic molecules, free diffusion over the BBB is impossible. Therefore, carbohydrates need to be transported into the nervous system via specialized transport proteins. In mammals, glucose transporter 1 (GLUT1, encoded by the Slc2a1 [solute carrier family 2 member 1] gene) is considered to be the main carbohydrate transporter in the BBB-forming endothelial cells. Aberrations in carbohydrate availability or transport are thought to be a major factor in the development of diverse neurological diseases such as GLUT1 deficiency syndrome, Alzheimer’s disease, and epilepsy (Arsov et al., 2012; Hoffmann et al., 2013; Kapogiannis and Mattson, 2011; Koepsell, 2020). Therefore, understanding the regulatory mechanisms that govern carbohydrate transport into the nervous system is of major interest. Interestingly, it has been reported that endothelial GLUT1 expression is increased upon hypoglycemia (Boado and Pardridge, 1993; Kumagai et al., 1995; Simpson et al., 1999, reviewed in Patching, 2017; Rehni and Dave, 2018). However, the molecular mechanisms that control this upregulation are not yet understood. In addition, upon oxygen or glucose deprivation, that are a consequence of ischemia, expression of the sodium glucose cotransporters SGLT1 (Slc5a1) and SGLT2 (Slc5a2) is induced in brain endothelial cells (Elfeber et al., 2004; Enerson and Drewes, 2006; Nishizaki et al., 1995; Nishizaki and Matsuoka, 1998; Vemula et al., 2009; Yu et al., 2013). Overall, this indicates that carbohydrate transport at the BBB can adapt to changes in carbohydrate availability in various ways. However, the molecular underpinnings of the different regulatory processes remain elusive.

As it is the case in vertebrates, the insect nervous system must be protected by a BBB. Since insects have an open circulatory system, the brain is not vascularized but is surrounded by the blood-like hemolymph. In Drosophila, the BBB surrounds the entire nervous system to prevent uncontrolled entry of hemolymph-derived substances. It is formed by two glial cell layers, the outer perineurial and inner subperineurial glial cells (reviewed in Limmer et al., 2014; Yildirim et al., 2019). The Drosophila BBB shares fundamental functional aspects with the vertebrate BBB. The subperineurial glial cells build a diffusion barrier by forming intercellular pleated septate junctions that prevent paracellular diffusion (Stork et al., 2008). In addition, efflux transporters export xenobiotics and many solute carrier family transporters supply the brain with essential ions and nutrients (DeSalvo et al., 2014; Hindle and Bainton, 2014; Lane and Treherne, 1972; Mayer and Belsham, 2009; Stork et al., 2008; reviewed in Weiler et al., 2017). In the Drosophila hemolymph, in addition to glucose, trehalose, a non-reducing disaccharide consisting of two glucose subunits linked by an α,α−1,1-glycosidic bond, is found in high quantities. Fructose is also present, albeit in low and highly fluctuating concentrations, making its nutritional role questionable (Blatt and Roces, 2001; Broughton et al., 2008; Lee and Park, 2004; Pasco and Léopold, 2012; Wyatt and Kalf, 1957). Transcriptome data of the BBB-forming glial cells suggests expression of several putative carbohydrate transporters (DeSalvo et al., 2014; Ho et al., 2019). The closest homologs of mammalian GLUT1–4 are dmGlut1, dmSut1, dmSut2, dmSut3, and CG7882. dmGlut1 has been shown to be expressed exclusively in neurons (Volkenhoff et al., 2018). In situ, microarray and single-cell sequencing data indicate very low or no expression for dmSut1-3 and CG7882 in the nervous system (Croset et al., 2018; Davie et al., 2018; Weiszmann et al., 2009). The carbohydrate transporter Tret1-1 (Trehalose transporter 1–1) is specifically expressed in perineurial glia (Volkenhoff et al., 2015). Tret1-1 is most homologous to mammalian GLUT6 and GLUT8 and has been shown to transport trehalose when heterologously expressed in Xenopus laevis oocytes (Kanamori et al., 2010).

The Drosophila nervous system, as the mammalian nervous system, is protected from growth defects caused by malnutrition through a process called brain sparing. It has been shown that Jelly belly (Jeb)/anaplastic lymphoma kinase (ALK) signaling constitutes an alternative growth-promoting pathway active in neuroblasts (neuronal stem cells) allowing their continuous division (reviewed in Lanet and Maurange, 2014; Cheng et al., 2011). However, if the brain continues developing and keeps its normal function, nutrient provision needs to be adapted to ensure sufficient uptake, even under challenging circumstances, like low circulating carbohydrate levels. How nutrient transport at the BBB is adapted to meet the needs of the nervous system even under nutrient restriction has not yet been studied.

Here, we show that carbohydrate transporter expression in Drosophila, as in mammals, adapts to changes in carbohydrate availability in circulation. Tret1-1 expression in perineurial glia of Drosophila larvae is strongly upregulated upon starvation. This upregulation is triggered by starvation-induced hypoglycemia as a mechanism protecting the nervous system from the effects of nutrient restriction. Ex vivo glucose uptake measurements using a genetically encoded Förster resonance energy transfer (FRET)-based glucose sensor show that the upregulation of carbohydrate transporter expression leads to an increase in carbohydrate uptake efficiency. The compensatory upregulation of Tret1-1 transcription is independent of insulin/adipokinetic hormone signaling, but instead depends on TGF-β signaling. This regulatory mechanism that protects the brain from the effects of malnutrition is likely conserved in mammals, since mammalian Glut1 is also upregulated in the BBB upon hypoglycemia and has been shown to be induced by TGF-β signaling in other tissues (Boado and Pardridge, 1993; Kumagai et al., 1995; Simpson et al., 1999; Lee et al., 2018).

Results

Tret1-1 is upregulated in perineurial glial cells upon starvation

The Drosophila larval brain is separated from circulation by the BBB to avoid uncontrolled leakage of hemolymph-derived potentially harmful substances. At the same time, the blood-brain barrier also separates the brain from nutrients available in the hemolymph. Thus, transport systems are necessary to ensure a constant supply of nutrients, including carbohydrates. The trehalose transporter Tret1-1 is expressed in the perineurial glial cells of the larval and adult nervous system (Volkenhoff et al., 2015). In order to better understand whether carbohydrate transport at the BBB is adapted to the metabolic state of the animal, we analyzed Tret1-1 dynamics under different physiological conditions. To do so we subjected larvae to chronic starvation applying a well-established paradigm that allows 40 hr of starvation without disturbing development (Figure 1AZinke et al., 2002). Seventy hour AEL larvae undergo an organismal change that allows their survival even under complete nutritional restriction (Beadle et al., 1938). Therefore, we starved animals before this timepoint to study the importance of Tret1-1 in a nutrient-dependent manner. In fed animals, Tret1-1 can be found at the plasma membrane of the perineurial glial cells (Figure 1B–E, Volkenhoff et al., 2015). However, a large portion of the protein localizes to intracellular vesicles (dotted structure in Figure 1E, Figure 2—figure supplement 1, Volkenhoff et al., 2015). Starvation increases Tret1-1 protein levels in perineurial glial cells (compare Figure 1D,E–D`,E`). Furthermore, more Tret1-1 protein can be found at the plasma membrane (Figure 1D`,E`, arrows, Figure 2—figure supplement 1). Whether the proportion of Tret1-1 at the plasma membrane is increased or if the increase in Tret1-1 at the plasma membrane is due to the general increase in Tret1-1 protein remains unclear.

Tret1-1 expression is upregulated upon starvation.

(A) Scheme of the starvation paradigm. Fed animals were kept for 96 hr on normal food before dissecting. Starved animals were transferred onto a water-soaked filter paper 56 hr after larval hatching. Forty hour later these animals were also dissected and immunohistochemistry was performed. (B–E) Brains of fed larvae expressing CD8-GFP in the subperineurial glial cells (Gli>>CD8-GFP) stained for GFP (green) and Tret1-1 (magenta/gray). (B`–E`) Brains of starved larvae with the same genotype. (D, D`) Tret1-1 expression in the perineurial glial cells is induced upon starvation. (E, E`) Close up of the BBB. Tret1-1 is localized in vesicles and its expression is elevated upon starvation. Tret1-1 is localized to the plasma membrane (arrows).

Intracellular trafficking of Tret1-1 is Rab7 and Rab10 dependent

Three mammalian glucose transporters, GLUT4, GLUT6, and GLUT8, are regulated via trafficking between storage vesicles and the plasma membrane (Corvera et al., 1994; Cushman and Wardzala, 1980; Lisinski et al., 2001; Suzuki and Kono, 1980). Similarly, a large amount of Tret1-1 localizes to intracellular vesicles (Figure 1E, Figure 2—figure supplement 1). Thus, intracellular trafficking of Tret1-1 may partially regulate carbohydrate uptake into the perineurial glial cells.

To analyze whether regulation of Tret1-1 expression requires intracellular trafficking, we studied the involvement of different Rab-GTPases. Utilizing an EYFP-Rab library available for Drosophila (Dunst et al., 2015), we found that subsets of Tret1-1-positive vesicles are also positive for Rab7, Rab10, Rab19, and Rab23 (Figure 2—figure supplement 1). Rab7 is needed for the formation of late endosomes and their fusion with lysosomes, while Rab10 has been implicated in GLUT4 storage vesicle trafficking in mammals (reviewed in Guerra and Bucci, 2016; Huotari and Helenius, 2011; Klip et al., 2019). The roles of Rab19 and Rab23 are less well understood. Rab23 has been implicated in planar cell polarity and in Hedgehog regulation in response to dietary changes, but its exact functions are unclear (Çiçek et al., 2016; Pataki et al., 2010). Rab19 has been described to act in enteroendocrine cell differentiation, but its role in this process is unknown (Nagy et al., 2017).

To determine a possible functional role of these Rab-GTPases in regulating Tret1-1 trafficking, we analyzed Tret1-1 localization in the background of a glia-specific knockdown (or expression of dominant-negative forms) of the respective Rab proteins (Figure 2A–G). Silencing of Rab19 or Rab23 did not induce any misregulation or mislocalization of Tret1-1 in perineurial glial cells (data not shown). In contrast, interfering with Rab7 or Rab10 function induced distinct abnormal phenotypes (Figure 2). Panglial knockdown of Rab7 using RNA interference reduced the levels of Tret1-1 (Figure 2B,B`). This phenotype was also observed when a dominant-negative form of Rab7, Rab7T22N was expressed in all glia (Figure 2F,F`). The dominant-negative Rab-constructs used here are tagged with an N-terminal YFP and thus induce a weak background staining in all glial cells (Figure 2F,G, asterisks). The effect of Rab seven knockdown on Tret1-1 was further verified by BBB-specific knockdown of Rab7 (Figure 2I). The reduced Tret1-1 level in Rab7 loss of function indicates that blocking late endosome to lysosome maturation and thus possibly blocking Tret1-1 degradation, induces a negative feedback that reduces Tret1-1 expression.

Figure 2 with 1 supplement see all
Tret1-1 intracellular trafficking depends on Rab7 and Rab10.

(A, C) Tret1-1 staining of the ventral nerve cord of glia-specific (repo-Gal4) knockdowns (A`, B`, C`, D`) shows a close up of the BBB. Dotted lines show the outline of the perineurial glia. (B, B`) Tret1-1 expression is strongly reduced by a glial Rab7 (Rab7JF02377) knockdown. (D, D`) Disrupting Rab10 expression in glia (Rab10GD13414) induces accumulation of Tret1-1 in the perineurial glia cytosol. (E–G`) Glial expression of the dominant-negative constructs Rab7T22N and Rab10T23N induce similar phenotypes as the RNA interference mediated knockdowns. (F, F`) Expressing Rab7T22N reduces Tret1-1 staining. (G, G`) Glia expression of Rab10T23N induces transporter mislocalization and a strong accumulation in the perineurial cytosol. (F–G`) The dominant-negative Rab-constructs are Rab-YFP fusions. Panglial overexpression thus leads to a weak background staining in the green channel (asterisks). (C) Tret1-1 staining of surface and cortex glia-specific knockdown using 46 F-Gal4 and Rab7JF02377 and Rab10GD13414. Loss of Rab7 reduces Tret1-1 staining, while Rab10 disruption induces transporter mislocalization.

In contrast to Rab7, knockdown of Rab10 in all glia, or in the BBB-glial cells specifically, leads to a prominent accumulation of Tret1-1 in the perineurial cytosol (Figure 2D,D`, J). This phenotype was reproduced when a dominant-negative form of Rab10, Rab10T23N, was expressed in glial cells (Figure 2G,G`). This suggests a major role of Rab10 in delivering Tret1-1 to the plasma membrane of perineurial glial cells. In summary, Tret1-1 homeostasis is dependent on Rab-GTPase-mediated intracellular trafficking.

Tret1-1 is transcriptionally regulated upon starvation

To test whether transcriptional regulation accounts for the strong increase in Tret1-1 protein upon starvation, we cloned the Tret1-1 promotor and established transgenic animals expressing either Gal4 or a nuclear GFP (stinger-GFP, stgGFP) under its control (Figure 3—figure supplement 1). We validated the expression induced by the promotor fragment by co-staining RFP expressed under Tret1-1-Gal4 control with the Tret1-1 antibody we generated previously (Volkenhoff et al., 2015). Tret1-1 promotor expression and Tret1-1 protein colocalize well in the nervous system (Figure 3—figure supplement 1B, arrows). We previously showed that Tret1-1 localizes to perineurial glial cells and some unidentified neurons (Figure 3—figure supplement 1B stars; Volkenhoff et al., 2015). To verify the perineurial glial expression of the Tret1-1 promotor, we stained Tret1-1-stgGFP animals for a nuclear perineurial glial marker, Apontic (Figure 3—figure supplement 1CZülbahar et al., 2018). Apontic and stgGFP colocalize in perineurial nuclei (Figure 3—figure supplement 1C, stars).

To analyze changes in Tret1-1 transcription levels, we subjected animals expressing stgGFP under the control of the Tret1-1 promotor to our starvation paradigm. Starvation induces a robust increase of stgGFP in the brains of starved larvae as quantified by western blot (Figure 3A,A`). To verify the upregulation of the Tret1-1 promotor, we additionally quantified stgGFP fluorescence in brain stainings. We normalized the GFP signal of individual nuclei to 4′,6-diamidino-2-phenylindole (DAPI), since it is highly unlikely that the DNA content of the nuclei would change upon starvation. The level of stgGFP expressed under Tret1-1 control is significantly higher in brains of starved animals compared to control larvae (Figure 3B). These experiments show that the Tret1-1 promotor is induced upon starvation and thus Tret1-1 levels are transcriptionally adapted to the animal’s metabolic state.

Figure 3 with 1 supplement see all
Tret1-1 is transcriptionally upregulated upon starvation.

(A) Tret1-1 is transcriptionally upregulated upon starvation since the Tret1-1 reporter Tret1-1>stgGFP is significantly upregulated in brains of starved compared to fed larvae as seen in western blots. Shown are images of representative western blots for anti-GFP and anti-tubulin (loading control). n=3 (A`) Quantification of Western blots. N=3. (B) Tret1-1 protein is significantly upregulated upon starvation in Tret1-1>stgGFP animals. Quantified is the GFP fluorescence normalized to DAPI in individual nuclei. N=5 , n > 34.

Increase in Tret1-1 expression upon starvation is sugar dependent

The expression of mammalian GLUT1 in brain endothelial cells increases upon chronic hypoglycemia (Boado and Pardridge, 1993; Kumagai et al., 1995; Rehni and Dave, 2018; Simpson et al., 1999). In Drosophila, starvation results in hypoglycemia (Dus et al., 2011; Matsuda et al., 2015). Thus, we wondered if the increase in Tret1-1 protein levels described here might be induced by a reduction in circulating carbohydrate levels. To understand whether dietary carbohydrates are sufficient to circumvent Tret1-1 induction, we compared animals fed on standard food (Figure 4A), starved animals (Figure 4A`), and animals fed on 10% sucrose in phosphate-buffered saline (Figure 4A``). Tret1-1 fluorescent intensity increases two to three times upon starvation compared to fed animals (Figure 4B). However, larvae kept on sugar-only food do not display increased Tret1-1 levels, but levels comparable to larvae kept on standard food (Figure 4A,A`, A``). The ratio of Tret1-1 intensity of animals kept on sugar food versus fed animals is around 1, indicating no increase in Tret1-1 signal (Figure 4B). Hence, dietary sugar abolishes Tret1-1 induction, indicating that other nutrients, like amino acids, are not important for Tret1-1 upregulation. Attempts to analyze Tret1-1 levels in larvae fed on a protein-only diet to study the influence of dietary amino acids were unsuccessful as larvae do not eat protein-only diet (no uptake of colored protein-only food into the intestine over 48 hr, data not shown). This data suggests that Tret1-1 is upregulated in the perineurial glial cells upon starvation-induced hypoglycemia. Hence, the Tret1-1 promoter fragment does include a starvation-sensitive motive.

Tret1-1 upregulation upon starvation is sugar-dependent.

(A- A``) Brains of larvae kept on normal food, under starvation conditions or on sugar food (10% sucrose) were stained for Tret1-1. (A`) Tret1-1 expression is elevated upon starvation of the animal. (A``) Dietary sugar reverses Tret1-1 upregulation completely. (B) Quantification of Tret1-1 expression in starved wild type animals and wild type animals on sugar food. The quantification shows the ratio of relative Tret1-1 fluorescence intensity in the perineurial glial cells of starved versus fed and sugar-fed vs. fed animals. N≥4; n=9-15; *p<0,05.

Glucose uptake rate increases upon starvation

Tret1-1 upregulation in perineurial glial cells is most likely a mechanism that ensures efficient carbohydrate uptake into the nervous system even under conditions of low circulating carbohydrate levels. Therefore, we aimed to study the impact of Tret1-1 upregulation on carbohydrate uptake. Kanamori et al., 2010 showed that Tret1-1 transports trehalose when heterologously expressed in X. laevis oocytes. Since not only trehalose, but also glucose and fructose, are found in the Drosophila hemolymph, we analyzed whether Tret1-1 also transports other carbohydrates. We expressed Tret1-1 in X. laevis oocytes to study its substrate specificity. The Tret1-1 antibody is specific to the Tret1-1 PA isoform, and thus at least this isoform is upregulated in the perineurial glial cells upon starvation. Therefore, we expressed a 3xHA-tagged version of Tret1-1PA in X. laevis oocytes. The functionality of this construct was verified by its ability to rescue the lethality associated with Tret1-1–/– mutants when ubiquitously expressed (using da-Gal4, Volkenhoff et al., 2015). Incubating X. laevis oocytes expressing Tret1-1PA-3xHA with different concentrations of 14C6-fructose, 14C6-glucose, or 14C12-trehalose for 60 min, we were able to verify the trehalose transport capacity reported previously (Kanamori et al., 2010Figure 5A). In addition, Tret1-1PA can facilitate uptake of glucose, while fructose is not taken up efficiently (Figure 5A).

Carbohydrate uptake rate into the surface glia is elevated upon starvation.

(A) Carbohydrate uptake capacity of Xenopus laevis oocytes heterologously expressing Tret1-1PA-3xHA. Tret1-1PA facilitates uptake of glucose and trehalose. In contrast, fructose uptake rate is minor. (B–C`) Expressing Tret1-1GD17787 in glial cells induces a loss of the specific Tret1-1 staining in perineurial glia. (C`) No increase upon starvation can be detected. (D) Glucose uptake was measured in ex vivo brains of fed or starved larvae using the genetically encoded glucose sensor FLII12Pglu-700µδ6. Shown are mean traces (n = 10). Error bars are standard error. (E) The glucose uptake rate is significantly higher in brains of starved control larvae compared to fed control larvae. Knocking down Tret1-1 prohibits the increased glucose uptake upon starvation. (F) In addition, the maximum intracellular glucose concentration is significantly higher in starved control larvae than in fed control larvae, suggesting that the uptake rate exceeds the rate of metabolism. This effect is also abolished when Tret1-1 is impaired in BBB-glia. N = 3, n ≥ 10.

Taking advantage of the glucose transport capacity of Tret1-1, we employed the Förster resonance energy transfer (FRET)-based glucose sensor FLII12Pglu-700µδ6 (Takanaga et al., 2008; Volkenhoff et al., 2018) to determine the effect of Tret1-1 upregulation on carbohydrate import into the living brain. A trehalose sensor to measure trehalose uptake is unfortunately not available. However, the glucose sensor allows live imaging of glucose uptake in a cell type of choice in ex vivo brain preparations (Volkenhoff et al., 2018). We expressed FLII12Pglu-700µδ6 specifically in the BBB-glial cells (9137-Gal4, DeSalvo et al., 2014). The respective larvae were subjected to the starvation protocol, and, subsequently, glucose uptake was measured (Figure 5D–F). The rate of glucose uptake was significantly increased in brains of starved animals compared to the brains of age-matched animals kept on standard food (Figure 5D,E). We now asked whether this elevated glucose uptake upon starvation is specifically caused by Tret1-1 upregulation. Therefore, we knocked down Tret1-1 expression in the BBB by expressing Tret1-1-dsRNA. Knockdown of Tret1-1 in glial cells leads to a loss of Tret1-1 staining, verifying the functionality of the construct (Figure 5C,C`). We measured glucose uptake into Tret1-1 knockdown brains. Indeed, the increase in glucose uptake is abolished when Tret1-1 is impaired (Figure 5E,F). Interestingly, fed Tret1-1 knockdown animals show somewhat elevated glucose levels compared to control animals (Figure 5E). Two additional sugar transporters, MFS3 and Pippin, have been shown to be expressed in the surface glia (McMullen et al., 2021). These transporters might be upregulated upon loss of Tret1-1 and overcompensate glucose transport in fed animals. In summary, these findings show that, indeed, carbohydrate uptake into the brain is more efficient in starved animals and that the elevated glucose uptake efficiency is dependent on Tret1-1 expression. Such improved carbohydrate uptake most likely protects the brain from the effects of low circulating carbohydrate levels.

Starvation-induced upregulation of Tret1-1 is insulin and adipokinetic hormone independent

The plasma membrane localization of mammalian GLUT4 is regulated by insulin (reviewed in Klip et al., 2019). Since starvation changes circulating carbohydrate levels, it has strong effects on insulin and adipokinetic hormone (AKH) signaling (reviewed in Nässel et al., 2015). Thus, insulin/AKH signaling may control Tret1-1 induction upon starvation. To study the implication of insulin signaling, we expressed dominant-negative forms of the insulin receptor (InR, InRK1409A, and InRR418P) in the BBB-forming glial cells (Figure 6A–C). If Insulin signaling was to directly regulate Tret1-1 transcription, one would assume a negative effect, since Tret1-1 is upregulated upon starvation when insulin levels are low. If insulin signaling indeed has a negative effect on Tret1-1 expression, higher Tret1-1 levels would be expected under fed conditions upon expression of a dominant-negative InR. Expression of dominant-negative forms of InR did not changed Tret1-1 levels in fed animals in comparison to the control (Figure 6A–C,A`-C`). In addition, Tret1-1 upregulation upon starvation was indistinguishable from that observed in control animals (Figure 6D), indicating that Tret1-1 transcription is independent of insulin signaling.

Figure 6 with 1 supplement see all
Tret1-1 regulation upon starvation is insulin and AKH independent.

(A–C`) Tret1-1 staining of the ventral nerve cord of starved and fed larvae expressing dominant-negative forms (InRK1409A or InRR418P) of the insulin receptor (InR) in the perineurial and subperineurial glial cells. (B, B`, C, C`) Tret1-1 levels in fed and starved animals expressing InR dominant negative are indistinguishable from wild type. (B`, C`) Tret1-1 upregulation upon starvation is seen in all cases. (D) Quantification of Tret1-1 upregulation in animals expressing InRK1409A or InRR418P. Shown is the ratio of relative Tret1-1 fluorescence intensity in the perineurial glial cells of starved versus fed animals. No significant differences between the genotypes are observed. N = 4, n = 12–16. (E–G`) Tret1-1 staining of the ventral nerve cord of starved and fed wild-type and Akh−/− mutant animals (AkhSAP or AkhAP). Tret1-1 levels in fed and starved mutant animals are indistinguishable from wild type. (F`, G`) Tret1-1 upregulation upon starvation can be seen in all mutants. (H) Quantification of Tret1-1 intensities of AkhSAP or AkhAP. Shown is the ratio of relative Tret1-1 fluorescence intensity in the perineurial glial cells of starved versus fed animals. No significant differences are observed. N = 3, n = 5–8.

In Drosophila, AKH is thought to play a role equivalent to glucagon/glucocorticoid signaling in mammals (Gáliková et al., 2015). AKH signaling induces lipid mobilization and foraging behavior, at least in the adult animal (Gáliková et al., 2015). Thus, AKH signaling would be a good candidate to induce Tret1-1 upregulation upon starvation. We analyzed Tret1-1 levels in Akh−/− (AkhSAP and AkhAP) mutant animals under normal conditions and starvation. Tret1-1 levels in the perineurial glial cells in both fed and starved Akh−/− mutant larvae are indistinguishable from control levels (Figure 6E–G,E`–G`). Interestingly, Tret1-1 is still induced upon starvation in Akh−/− mutant animals (Figure 6H). This suggests that AKH does not play a role in Tret1-1 regulation upon starvation. In summary, the core signaling pathways regulating organismal nutrient homeostasis, Insulin and AKH signaling, are not involved in Tret1-1 upregulation upon starvation.

Jeb/ALK signaling does not regulate Tret1-1 expression

Tret1-1 upregulation upon starvation is likely a mechanism to spare the nervous system from the effects of restricted nutrient availability. Jeb/ALK signaling is important to allow continued developmental brain growth even upon poor nutrition (Cheng et al., 2011). To analyze whether this pathway might also play a role in adapting carbohydrate transport, we knocked down jeb and Alk in all glial cells and analyzed Tret1-1 expression. Alk knockdown in glial cells did not induce changes in Tret1-1 expression compared to control animals (Figure 6—figure supplement 1). Tret1-1 is still upregulated upon starvation, indicating that ALK signaling in glial cells is not involved in Tret1-1 regulation (Figure 6—figure supplement 1B,B`). jeb knockdown in all glial cells induced strong starvation susceptibility of the animals in our hands. Most animals died within the 40 hr starvation period, which does not happen to control animals. Analysis of Tret1-1 expression in the perineurial glial cells of escapers did not give coherent results. Nevertheless, since Alk knockdown shows wild typic Tret1-1 upregulation, Jeb/ALK signaling is most likely not implicated in the regulation of carbohydrate transport upon starvation.

Transforming growth factor β signaling regulates Tret1-1 expression

In Drosophila, both TGF-β/activin signaling and TGF-β/bone morphogenetic protein (BMP) signaling have been implicated in metabolic regulation (Ballard et al., 2010; Ghosh and O'Connor, 2014). The activin and BMP branches of TGF-β signaling share some components, like the type II receptors Punt (Put) and Wishful thinking (Wit) and the co-Smad Medea, while other components are specific to one or the other branch (reviewed in Upadhyay et al., 2017, Figure 7K).

Tret1-1 upregulation upon starvation is BMP-mediated TGF-β signaling dependent.

(A, A`, I, I`) Tret1-1 staining of the ventral nerve cord of starved and fed control (repo>>mCherry-dsRNA) animals and animals with a glial TGF-β knockdown. (B, B`, C, C`) Knockdown of the type I receptor Put in glial cells using two different dsRNA constructs (putGD2545 and putKK102676) abolished Tret1-1 upregulation upon starvation. (D, D`) Glia-specific knockdown of wit using witKK100911 does not affect Tret1-1 upregulation upon starvation. (F, F`) Glia-specific knockdown of the activin-branch-specific type II receptor Babo (using baboNIG8224R-1) does not have any influence on Tret1-1 upregulation upon starvation (compare to control in E, E`). (G, G`, H, H`) The glia-specific knockdown of the BMP-branch-specific type II receptor Sax (using saxGD2546 and saxGD50) does not influence Tret1-1 expression (compare to control in E, E`). (I, I`) In contrast, glia-specific knockdown of the main BMP-branch-specific type II receptor Tkv (using tkvKK1023019) abolishes Tret1-1 upregulation upon starvation (compare to control in E, E`). This indicates that signaling via the BMP branch of TGF-β signaling regulates Tret1-1 induction upon starvation. (J) Quantification of Tret1-1 upregulation upon starvation. Shown is the ratio of relative Tret1-1 fluorescence intensity in the perineurial glial cells of starved versus fed animals. N ≥ 4, n = 10–22. (K) Schematic representation of the two branches of the TGF-β signaling pathway.

Since Put has been implicated in regulating carbohydrate homeostasis, we asked if Put-dependent TGF-β signaling could also play a role in carbohydrate-dependent Tret1-1 regulation. Thus, we expressed dsRNA constructs against put in a glia-specific manner and analyzed Tret1-1 levels in the perineurial glial cells of fed and starved animals (Figure 7B,B`,C,C`). Indeed, starvation-dependent upregulation of Tret1-1 was completely abolished upon put knockdown in glial cells using either putKK102676 or putGD2545. Quantification shows no upregulation of Tret1-1 upon starvation in put knockdown animals (Figure 7J). In contrast, knockdown of wit using witKK100911 did not affect Tret1-1 upregulation upon starvation (Figure 7D,D`). This data suggests that Put-dependent TGF-β signaling in glia is essential for starvation-induced upregulation of Tret1-1.

The activin-branch of TGF-β signaling has been shown to be important for sugar sensing and sugar metabolism in the adult fly as well as in larvae (Chng et al., 2014; Ghosh and O'Connor, 2014; Mattila et al., 2015). The type I receptor Baboon (Babo) is specific for the activin branch of TGF-β signaling (reviewed in Upadhyay et al., 2017; Figure 7F,F`). To test this, we silenced babo in glial cells using baboNIG8224R that has been shown to efficiently abolish babo expression (Hevia and de Celis, 2013). Interestingly, in babo knockdown animals Tret1-1 expression is strongly upregulated upon starvation (Figure 7J), indicating that the Activin branch of TGF-β signaling is not implicated in Tret1-1 regulation.

This indicates that the BMP-branch of TGF-β signaling is implicated in Tret1-1 regulation. To analyze its involvement, we knocked down the BMP-branch-specific type I receptors Thickveins (Tkv) and Saxophone (Sax) (reviewed in Upadhyay et al., 2017). Loss-of-function mutations in both tkv and sax are lethal, but Tkv overexpression can rescue sax loss-of-function; thus Tkv seems to be the primary type I receptor in the BMP-branch of TGF-β signaling (Brummel et al., 1994). Glia-specific knockdown of sax using saxGD50 or saxGD2546 did not show any differences in Tret1-1 regulation upon starvation compared to control knockdown animals (Figure 7G,G`,H,H`). In contrast, knockdown of tkv using tkvKK102319 abolished Tret1-1 upregulation upon starvation, highlighting its importance for signaling (Figure 7I,I`).

Glass-bottom boat-mediated TGF-β signaling induces Tret1-1 expression upon starvation

The BMP branch of TGF-β signaling can be activated by several ligands: glass-bottom boat (Gbb), decapentaplegic (Dpp), screw (Scw), and most likely Maverick (Mav) (reviewed in Upadhyay et al., 2017). Of those ligands, only Gbb has been implicated in regulating metabolic processes to date (reviewed in Upadhyay et al., 2017). gbb−/− mutant animals show a phenotype that resembles the state of starvation, including reduced triacylglyceride storage and lower circulating carbohydrate levels (Ballard et al., 2010). It has previously been shown that overexpression of Gbb in the fat body leads to higher levels of circulating carbohydrates and thus the opposite of a starvation-like phenotype (Hong et al., 2016). Thus, to study their role in Tret1-1 regulation, we over-expressed Gbb or Dpp locally in the surface glial cells (9137-Gal4, perineurial and subperineurial glial cells) to avoid strong systemic impact that would counteract the effects of starvation (Figure 8A–C). In fed animals that express Gbb in the BBB cells, Tret1-1 expression is significantly upregulated in the perineurial glial cells (Figure 8B,D). This effect is specific to Gbb, since neither GFP-expressing control animals nor Dpp-expressing animals display this effect (Figure 8A,B,D). This shows that Gbb-dependent signaling does induce Tret1-1 upregulation. Furthermore, we analyzed the expression of Gbb, using antibodies (Akiyama et al., 2012). Gbb is found in the Tret1-1-expressing perineurial glial cells but seems to be also expressed in other glial cell types (most likely subperineurial glia and cortex glia) in the nervous system (Figure 8G`). Upon starvation, not only Tret1-1 but also Gbb expression is increased in the nervous system (Figure 8H`, I`).

Tret1-1 upregulation depends on Gbb-mediated signaling.

(A–C) Tret1-1 staining of the ventral nerve cord of fed control (9137>>GFP) animals or animals overexpressing either Gbb or Dpp in the perineurial and subperineurial glial cells (using 9137-Gal4). (B) Overexpression of Gbb induces increased Tret1-1 expression in fed animals. (C) Differently, overexpression of Dpp does not have any effect on the Tret1-1 expression. (D) Quantification of Tret1-1 upregulation upon overexpression of Gbb or Dpp in fed animals. The quantification shows Tret1-1 expression levels in the perineurial glial cells normalized to those in controls (9137>>GFP). N = 4; n = 20–25; (E–F``) Gbb is expressed in perineurial glial cells (coexpression with Tret1-1) and in other glial cell types, most likely subperineurial glial cells and cortex glial cells. (G–H`) Upon starvation expression of Tret1-1 and Gbb is increased in the VNC. (I) Quantification of Gbb upregulation upon starvation in the brain. N = 5; n > 17.

Taken together, the data reported here show that, upon starvation, increased levels of Gbb are found in the ventral nerve cord. Gbb activates the BMP-branch of TGF-β signaling in the perineurial glial cells, via the receptors Tkv (type I) and Put (type II), and induces Tret1-1 expression. Since it has been shown that mammalian GLUT1 is also upregulated upon hypoglycemia, it will be interesting to see whether TGF-β signaling is conserved as a pathway adapting carbohydrate transport to changes in nutrient availability.

Discussion

The nervous system is separated from circulation by the BBB. This separation on the one hand protects the nervous system form circulation-derived harmful substances, but on the other hand necessitates efficient nutrient transport to ensure neuronal function. Since the nervous system mainly uses carbohydrates to meet its energetic demands, carbohydrates need to be taken up at a sufficient rate. We previously showed that the carbohydrate transporter Tret1-1 is specifically expressed in perineurial glial cells that surround the Drosophila brain and that glucose is taken up into the nervous system (Volkenhoff et al., 2018; Volkenhoff et al., 2015). Here, we investigated how Tret1-1-mediated carbohydrate uptake into the nervous system is adapted to the metabolic state of the animal to spare the nervous system from the effects of malnutrition. We show that Tret1-1 is a carbohydrate transporter that cannot only facilitate transport of trehalose as previously reported (Kanamori et al., 2010), but also of glucose (Figure 5). Upon chronic starvation, Tret1-1 protein levels are increased in the perineurial glial cells (Figure 3), boosting the glucose transport capacity in those cells (Figure 5). This effect reverts when Tret1-1 is knocked down (Figure 5), suggesting that Tret1-1 upregulation is crucial for adapting carbohydrate transport to adverse conditions. Lipoprotein particles were shown to be able to cross the BBB (Brankatschk and Eaton, 2010). An increase in lipid uptake and a partial switch to lipid usage for gaining energy might take place in addition to Tret1-1 upregulation and most likely upon longer phases of nutrient restrictions. Such metabolic changes would then most likely also have an effect on insulin signaling (Brankatschk et al., 2014).

Subcellular trafficking of Tret1-1, and its integration into the plasma membrane, is important for Tret1-1 homeostasis (Figure 2). Loss of Rab7 or Rab10 function has severe effects on Tret1-1 levels or localization (Figure 2). The intracellular accumulation of Tret1-1 induced by Rab10 silencing indicates that Tret1-1 cannot be properly delivered to the plasma membrane. Loss of Rab10 function in mammalian adipocytes induces perinuclear accumulation of GLUT4, suggesting regulatory parallels between Tret1-1 and GLUT4 (Sano et al., 2007). GLUT4 (Slc2a4) is weakly expressed in the mammalian BBB (James et al., 1988; McCall et al., 1997). Also, the two closest GLUT homologs of Tret1-1, GLUT6 and GLUT8, are regulated by subcellular trafficking from cytoplasmic storage vesicle to the plasma membrane (Lisinski et al., 2001). Both GLUT6 and GLUT8 are expressed in the mammalian brain, but their roles are unclear (Doege et al., 2000a; Doege et al., 2000b; Ibberson et al., 2000; Reagan et al., 2002).

We show that the Tret1-1 promoter is induced upon starvation (Figure 3). This suggests that the Tret1-1 locus harbors a starvation-responsive element. Tret1-1 levels are most likely regulated dependent on carbohydrate availability since animals feeding on sugar-only food do not show an upregulation of Tret1-1 (Figure 4). It has been reported that insulin-induced hypoglycemia leads to an upregulation of GLUT1 mRNA as well as protein in rat BBB-forming endothelial cells (Kumagai et al., 1995). In isolated rat brain microvessels, insulin-induced hypoglycemia also activates upregulation of GLUT1 protein levels and in addition an accumulation of GLUT1 at the luminal membrane (Simpson et al., 1999). In these rodent studies, GLUT1 upregulation was detected upon insulin injection that induces hypoglycemia. Under starvation conditions that lead to hypoglycemia in our experimental setup, however, insulin levels are strongly reduced. If under high-insulin conditions GLUT1 levels are increased in mammals, this increase cannot be triggered by a loss of insulin. Along the same lines, the upregulation of Tret1-1 in perineurial glial cells we report here is independent of insulin signaling as well as AKH signaling (Figure 6). Thus, the regulatory mechanisms reported here may be conserved. This is especially interesting since aberrations in GLUT1 functionality or levels can cause severe diseases, such as GLUT1 deficiency syndrome or Alzheimer’s (reviewed in Koepsell, 2020). Therefore, understanding the mechanisms that control the expression of carbohydrate transporters in the BBB-forming cells may be the basis for developing a treatment that allows to correct insufficient transporter expression in such diseases.

The induction of carbohydrate transport at the BBB upon hypoglycemia or starvation seems to be a mechanism that is required to spare the brain from the effects of malnutrition. It has previously been shown in mammals, as well as in flies, that the developing nervous system is protected from such effects to allow proper brain growth, while other organs undergo severe growth restriction. This process is called asymmetric intra-uterine growth restriction in humans or ‘brain sparing’ in model organisms (reviewed in Lanet and Maurange, 2014). In Drosophila, the mechanisms that underly the protection of the brain have been studied. Here, Jeb/ALK signaling in the neuroblast niche circumvents the need for insulin signaling to propagate growth (reviewed in Lanet and Maurange, 2014). Interestingly, Jeb/ALK signaling is not the basis for Tret1-1 upregulation in the perineurial glial cells, since glial ALK knockdown does not abolish Tret1-1 induction upon starvation (Figure 6—figure supplement 1).

TGF-β signaling has been shown to be involved in metabolic regulation in vertebrates and invertebrates (Andersson et al., 2008; Bertolino et al., 2008; Ghosh and O'Connor, 2014; Zamani and Brown, 2011). In Drosophila, the Activin-like ligand Dawdle (Daw) as well as the BMP ligand Glass-bottom boat (Gbb) have been implicated in metabolic regulation (reviewed in Upadhyay et al., 2017). Daw seems to be one of the primary players in the conserved ChREBP/MondoA-Mlx complex-dependent sugar-sensing pathway (Mattila et al., 2015). However, since the activin-like branch of TGF-β signaling does not play a role in Tret1-1 regulation, it does not seem to affect carbohydrate uptake into the nervous system. The BMP ligand Gbb, on the other hand, has been implicated in nutrient storage regulation. gbb mutants show expression defects of several starvation response genes (Ballard et al., 2010). Furthermore, the fat body of fed gbb mutants resembles that of starved wild-type animals by its nutrient storage and morphology (Ballard et al., 2010). Gbb seems to regulate nutrient storage in the fat body and control fat body morphology in a cell-autonomous manner. Additionally, since gbb mutants display increased nutrient uptake rates, gbb signaling also has systemic effects that are not yet completely understood (Ballard et al., 2010; Hong et al., 2016). We show here that upon starvation-elevated levels of Gbb signaling in the VNC induce an upregulation of Tret1-1 expression in perineurial glial cells (Figure 8). Gbb signals via Tkv and Put to regulate Tret1-1 expression upon starvation (Figure 7). Gbb was shown to act as proliferation factor in neuroblasts and also as a paracrine survival signal in perineurial glia (Kanai et al., 2018). However, we report here that Gbb is also expressed in other glial subtypes (Figure 8). Interestingly, it has been shown that BMP signaling induces transcriptional upregulation of GLUT1 in chondrocytes during murine skeletal development (Lee et al., 2018). Thus, TGF-β-dependent regulation of carbohydrate transport at the BBB may be based on the same mechanisms and consequently be evolutionarily conserved.

Interestingly, the transcription of the Drosophila sodium/solute cotransporter cupcake has also been shown to be upregulated upon starvation. Cupcake is expressed in some ellipsoid body neurons upon starvation and is essential for the ability of the animal to choose feeding on a nutritive sugar over feeding on a sweeter non-nutritive sugar after a period of nutrient deprivation (Park et al., 2016). Furthermore, several solute carrier family members have been shown to be regulated by carbohydrate availability in mouse cortical cell culture (Ceder et al., 2020). It will be very interesting to investigate whether such transcriptional upregulation is also mediated by TGF-β signaling and whether TGF-β-mediated transcriptional regulation in the nervous system is a central mechanism that allows survival under nutrient shortage.

In summary, we report here a potentially conserved mechanism that protects the nervous system from effects of nutrient shortage by upregulation of carbohydrate transport at the BBB. This upregulation renders carbohydrate uptake more efficient and allows sufficient carbohydrate uptake even when circulating carbohydrate levels are low. In Drosophila, compensatory upregulation of Tret1-1 is regulated via Gbb and the BMP branch of TGF-β signaling. This mechanism is likely to be evolutionarily conserved, since mammalian GLUT1 has been shown to be regulated via BMP signaling in other tissues (Lee et al., 2018). These findings may serve as the basis of a future treatment against diseases caused by insufficient carbohydrate transport in the nervous system.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Gene (Drosophila melanogaster)Tret1-1FBgn0050035
Genetic reagent (D. melanogaster)jebKK111857Vienna Drosophila Resource Centerv103047;
FBgn0086677;
FBst0474909
Genetic reagent (D. melanogaster)jebGD5472Vienna Drosophila Resource Centerv30800;
FBgn0086677;
FBst0458662
Genetic reagent (D. melanogaster)AlkGD42Vienna Drosophila Resource Centerv11446;
FBgn0040505;
FBst0450267
Genetic reagent (D. melanogaster)putKK102676Vienna Drosophila Resource Centerv107071;
FBgn0003169;
FBst0478894
Genetic reagent (D. melanogaster)putGD2545Vienna Drosophila Resource Centerv37279;
FBgn0003169;
FBst0461929
Genetic reagent (D. melanogaster)witKK100911Vienna Drosophila Resource Centerv103808;
FBgn0024179;
FBst0475666
Genetic reagent (D. melanogaster)saxGD50Vienna Drosophila Resource Centerv42457;
FBgn0003317;
FBst0464598
Genetic reagent (D. melanogaster)saxGD2546Vienna Drosophila Resource CenterFBgn0003317
Genetic reagent (D. melanogaster)tkvKK102319Vienna Drosophila Resource Centerv105834;
FBgn0003716;
FBst0477660
Genetic reagent (D. melanogaster)Rab10GD13414Vienna Drosophila Resource Centerv28758;
FBgn0015789;
FBst0457628
Genetic reagent (D. melanogaster)Rab10GD16778Vienna Drosophila Resource Centerv46792;
FBgn0015789;
FBst0466897
genetic reagent (D. melanogaster)Rab10KK109210Vienna Drosophila Resource Centerv101454;
FBgn0015789;
FBst0473327
Genetic reagent (D. melanogaster)Tret1-1GD17787Vienna Drosophila Resource Centerv52360;
FBgn0050035;
FBst0469787
Genetic reagent (D. melanogaster)Rab7T22NBloomington Drosophila Stock Center9778;
FBgn0015795
Genetic reagent (D. melanogaster)Rab10T23NBloomington Drosophila Stock Center9778;
FBgn0015795;
FBst0009778
Genetic reagent (D. melanogaster)Rab7EYFPBloomington Drosophila Stock Center62545;
FBgn0015795;
FBst0062545
Genetic reagent (D. melanogaster)Rab10EYFPBloomington Drosophila
Stock Center
62548;
FBgn0015789;
FBst0062548
Genetic reagent (D. melanogaster)Rab19EYFPBloomington Drosophila Stock Center62552;
FBgn0015793;
FBst0062552
Genetic reagent (D. melanogaster)Rab23EYFPBloomington Drosophila Stock Center62554;
FBgn0037364;
FBst0062554
Genetic reagent (D. melanogaster)Rab7TRIP.JF02377Bloomington Drosophila Stock Center27051;
FBgn0015795;
FBst0027051
Genetic reagent (D. melanogaster)InRK1409ABloomington Drosophila Stock CenterFBgn0283499
Genetic reagent (D. melanogaster)InRR418PBloomington Drosophila Stock CenterFBgn0283499
Genetic reagent (D. melanogaster)UAS-dppBloomington Drosophila Stock Center1486;
FBgn0000490
Genetic reagent (D. melanogaster)CherrydsRNABloomington Drosophila Stock Center35785;
FBti0143385
Genetic reagent (D. melanogaster)UAS-CD8-GFPBloomington Drosophila Stock Center30002 or 30003
Genetic reagent (D. melanogaster)AkhAPGáliková et al., 2015
doi: 10.1534/genetics.115.178897
FBal0319564
Genetic reagent (D. melanogaster)AkhSAPGáliková et al., 2015
doi: 10.1534/genetics.115.178897
FBal0319565
Genetic reagent (D. melanogaster)baboNIG8224RJapanese National Institute of GeneticsFBal0275907
Genetic reagent (D. melanogaster)gliotactin-Gal4Sepp et al., 2001
Doi: 10.1006/dbio.2001.0411
Genetic reagent (D. melanogaster)repo-Gal4Sepp et al., 2001
Doi: 10.1006/dbio.2001.0411
Genetic reagent (D. melanogaster)46 F-Gal4Xie and Auld, 2011
Doi: 10.1242/dev.064816
Genetic reagent (D. melanogaster)9137-Gal4DeSalvo et al., 2014
Doi: 10.3389/fnins.2014.00346
Genetic reagent (D. melanogaster)UAS-FLII12Pglu-700µδ6Volkenhoff et al., 2018
Doi: 10.1016/j.jinsphys.2017.07.010
Maintained at S. Schirmeier lab
Genetic reagent (D. melanogaster)UAS-GbbP. Soba
Genetic reagent (D. melanogaster)UAS-RFPS. Heuser
Genetic reagent (D. melanogaster)w1118Lindsley and Zimm, 1992
ISBN 9780124509900
Genetic reagent (D. melanogaster)Tret1-1-stGFPThis paperMaintained at S. SchirmeierTret1-1 promoter fusion to a nuclei-targeted GFP
Genetic reagent (D. melanogaster)Tret1-1-Gal4This paperMaintained at S. SchirmeierTret1-1 promoter induced Gal4 expression
Antibodyanti-Tret1-1
guinea pig polyclonal
Volkenhoff et al., 2015Maintained at S. Schirmeier Lab(1:50)
Antibodyanti-Laminin rabbit polyclonalAbcamab11575(1:1000)
Antibodyanti-Repo mouse monoclonalDevelopmental Studies Hybridoma Bank8D12 anti-Repo(1:2)
Antibodyanti-GFP mouse monoclonalMolecular ProbesA11120(1:1000)
Antibodyanti-GFP chicken polyclonalAbcamAb92456(1:1000)
Antibodyanti-GFP JL-8
mouse monoclonal
ClontechCat. 632381(1:10000) WB
Antibodyanti-Tubulin mouse monoclonalDevelopmental Studies Hybridoma Bank12G10 anti-alpha-tubulin(1:80) WB
Antibodyanti-Apontic rabbit polyclonalEulenberg and Schuh, 1997Gifted from Reinhard Schuh(1:150)
Antibodyanti-Gbb mouse monoclonalDevelopmental Studies Hybridoma BankGBB 3D6-24(1:20)
Recombinant DNA reagentpBPGuw-stingerGFP (vector)C. Klämbt
Recombinant DNA reagentpBPGuwGal4 (vector)Addgene17575
Recombinant DNA reagentpGEM-He-Juel
(vector)
S. Bröer
Sequence-based reagentForward primer_Tret1-1promThis paperPCR primersCACCGGTCTCAAGCTCTCTTTTTTGCCTTACATATTTT
Sequence-based reagentReverse primer_Tret1-1promThis paperPCR primersTGGGTAAGTTGGAGAGAGAG
Sequence-based reagentForward primer
Tret1-1 PA
This paperPCR primersCGTCTAGAATGAGTGGACGCGAC
Peptide, recombinant proteinReverse primer Tret1-1 PAThis paperPCR primersCGAAGCTTCTAGCTTACGTCACGT
Commercial assay or kitpENTR/D- TOPO Cloning KitThermo Fisher ScientificK240020
Commercial assay or kitmMESSAGE mMACHINE T7 KitThermo Fisher ScientificAM1344
Chemical compound, drug14C12-trehaloseHartmann Analytic, Braunschweig#1249
Chemical compound, drug14C6-glucoseBiotrend, Köln#MC144-50
Chemical compound, drug14C6-fructoseBiotrend, Köln#MC1459-50
Chemical compound, drugRotiszint eco plus scintillation cocktailCarl RothArt. No. 0016.3
Software, algorithmSigmaPlotJadelSPSS Inc
Software, algorithmFijiNIH

Fly stocks

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Flies were kept at 25°C on a standard diet if not noted otherwise. The following fly stocks were used in this study: jebKK111857, jebGD5472, AlkGD42, putKK102676, putGD2545, witKK100911, saxGD50, saxGD2546, tkvKK102319, Rab10GD13414, Rab10GD16778, Rab10KK109210, Tret1-1GD17787(all fly stocks were obtained from VDRC Fly Center). Rab7T22N, Rab10T23N, Rab7EYFP, Rab10EYFP, Rab19EYFP, Rab23EYFP, Rab7TRIP.JF02377, InRK1409A, InRR418P, UAS-dpp (BDSC 1486), CherrydsRNA (BDSC 35785), UAS-CD8-GFP (BDSC 30002 or 30003) (all fly stocks were obtained from Bloomington Drosophila Stock Center). AkhAP and AkhSAP (Gáliková et al., 2015), baboNIG8224R (Japanese National Institute of Genetics), gliotactin-Gal4, repo-Gal4 (Sepp et al., 2001), 46 F-Gal4 (Xie and Auld, 2011), 9137-Gal4 (DeSalvo et al., 2014), UAS-FLII12Pglu-700µδ6 (Volkenhoff et al., 2018), UAS-Gbb (P. Soba), UAS-RFP (S. Heuser), w1118 (Lindsley and Zimm, 1992).

Creation of Tret1-1-Gal4 and Tret1-1-stinger-GFP flies

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For creation of Tret1-1-Gal4 and Tret1-1-stinger-GFP flies, first the promotor region of Tret1-1 was cloned from genomic DNA (forward primer_Tret1-1prom: CACCGGTCTCAAGCTCTCTTTTTTGCCTTACATATTTT, reverse primer_Tret1-1prom: TGGGTAAGTTGGAGAGAGAG) into the pENTR vector using the pENTR/D-TOPO Cloning Kit (Thermo Fisher Scientific). Via the gateway system, the promotor fragment was cloned either into the pBPGuwGal4 vector (Addgene #17575) or into pBPGuw-stingerGFP. Both clones were introduced into the 86Fb landing site via Φ integrase-mediated transgenesis (Bischof et al., 2013).

Immunohistochemistry, SDS–PAGE, and western blotting

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Third-instar larval brains or larval brains of animals that had been subjected to the larval starvation protocol were dissected and immunostained following standard protocols (Volkenhoff et al., 2015). Specimen were analyzed using the Zeiss 710 LSM or the Zeiss 880 LSM and the Airy Scan Module (Zeiss, Oberkochen, Germany). SDS–PAGE and western blotting were performed following published protocols (Zobel et al., 2015). Lysates were generated from 96 hr ± 3 hr old larval brains.

The following antibodies were used: guinea pig anti-Tret1-1 (1:50, Volkenhoff et al., 2015), rabbit anti-Laminin (1:1000, Abcam), mouse anti-Repo (1:2, Developmental Studies Hybridoma Bank), mouse anti-GFP (for immunohistochemistry: 1:1000, Molecular Probes; for western blotting: 1:10,000, Clontech), chicken anti-GFP (1:1000, Abcam), mouse anti-Tubulin (1:80, Developmental Studies Hybridoma Bank), rabbit anti-Apontic (1:150, Eulenberg and Schuh, 1997), mouse anti-Gbb (1:20, Developmental Studies Hybridoma Bank). As secondary conjugated antibodies, Alexa488- (1:1000), Alexa568- (1:1000), and Alexa647-coupled (1:500) antibodies were used (all from Thermo Fisher Scientific). For western blotting, goat anti-mouse HRP (Dianova, 1:7500) was used. HRP activity was detected using the ECL detection system kit (GE Healthcare) and the Amersham Imager 680 (GE Healthcare). Image analysis was performed using the Fiji plugin of ImageJ (1.52 p, java 1.8.0._172 64-bit, NIH, Bethesda, MD). N gives the number of independent experiments; n is the total number of animals analyzed.

Larval starvation

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Flies were kept overnight on standard food to stage the embryos. Fifty-six hours after larval hatching similar-sized larvae were collected, cleared from food, and transferred to different food conditions: standard food, water-soaked filter paper, or 10% sucrose in phosphate-buffered saline. They were kept for 40 hr on this condition before dissecting.

For fluorescent analysis, mean gray values of a region of interest (ROI) containing the entire tip of the ventral nerve cord were measured. The mean of values of seven single planes was taken of each brain and normalized to the size of the ROI. To obtain comparable values between experiments, the ratio of values received from starved animals to the mean of fed animals was calculated. Statistical analysis was performed using Sigma Plot software (Jadel). Differences were assessed by the Mann–Whitney rank sum test or t-test. p-values<0.05 were considered as significantly different.

Measurement of glucose uptake

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Larvae expressing UAS-FLII12Pglu-700µδ6 FRET glucose sensor under the control of 9137-Gal4 and either mCherry-dsRNA or Tret1-1-dsRNA were kept on standard food or under starvation conditions following the larval starvation protocol. Larval brains were subsequently dissected in HL3 buffer (70 mM NaCl, 5 mM KCl, 20 mM MgCl2, 10 mM NaHCO3, 115 mM sucrose, 5 mM trehalose, 5 mM HEPES; pH 7.2; ca. 350 mOsm) and adhered to poly-d-lysine-coated coverslips. Coverslips were secured into a flow through chamber and mounted to the stage of a LSM880 confocal microscope (Zeiss, Oberkochen, Germany). The chamber was then connected to a mini-peristaltic pump (MPII, Harvard Apparatus) to allow buffer exchange.

Fluorescent images were acquired immediately after dissection using 20×/1.0 DIC M27 75 mm emersion objective (Zeiss, Oberkochen, Germany), with excitation 436/25 nm, beam splitter 455 nm, emission 480/40 nm (CFP channel); excitation 436/25 nm, beam splitter 455 nm, emission 535/30 nm (YFP channel). Each larval brain was imaged in a separate experiment (n = 10). After 2.5 min, HL3 buffer was exchanged for glucose buffer (HL3 supplemented with 10 mM glucose; pH 7.2) and replaced by HL3 again after a further 7.5 min.

For data analysis, a ROI containing the entire larval brain was selected and the mean gray value of all pixels minus background for each channel was calculated. Values were normalized to known minimum (HL3 buffer). Statistical and regression analysis of data obtained was performed using SigmaPlot software (Jandel). To determine glucose uptake rates, 10 time points 9 s after values rose above baseline levels were used to calculate the linear slope of each curve. Differences were assessed by the Mann–Whitney rank sum test (pairs). p-values<0.05 were considered as significantly different.

Xenopus experiments

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For isolation of oocytes, female X. laevis frogs (purchased from the Radboud University, Nijmegen, Netherlands) were anesthetized with 1 g/l of ethyl 3-aminobenzoate methanesulfonate and rendered hypothermic. Parts of ovarian lobules were surgically removed under sterile conditions. The procedure was approved by the Landesuntersuchungsamt Rheinland-Pfalz, Koblenz (23 177–07/A07-2-003 §6). Oocytes were singularized by collagenase treatment in Ca2+-free oocyte saline (82.5 mM NaCl, 2.5 mM KCl, 1 mM MgCl2, 1 mM Na2HPO4, 5 mM HEPES, pH 7.8, 2 mg/l gentamicin) at 28°C for 2 hr. The singularized oocytes were stored overnight at 18°C in Ca2+-containing oocyte saline (82.5 mM NaCl, 2.5 mM KCl, 1 mM CaCl2, 1 mM MgCl2, 1 mM Na2HPO4, 5 mM HEPES, pH 7.8, 2 mg/l gentamicin). The procedure was described in detail previously (Becker et al., 2014).

For heterologous protein expression in X. laevis oocytes the D. melanogaster cDNA sequences of Tret1-1 isoform A was amplified via PCR from pUAST-Tret1-1-PA-3xHA plasmid (forward primer_Tret1-1PA: CGTCTAGAATGAGTGGACGCGAC, reverse primer_Tret1-1PA: CGAAGCTTCTAGCTTACGTCACGT) and cloned into the pGEM-He-Juel vector using XbaI/ HindIII restriction sites. cRNA was produced by in vitro transcription using the mMESSAGE mMACHINE T7 Kit (Thermo Fisher Scientific). Oocytes of the stages V and VI were injected with 18 ng (for mass spectrometry) to 20 ng (for scintillation analysis) of cRNA, and measurements were carried out three to six days after cRNA injection.

To analyze the transport capacity by scintillation measurements, radioactive sugar substrates were generated using unlabeled sugar solutions of different concentrations in oocyte saline and adding 14C-labeled sugar at a concentration of 0.15 μCi/100 μl (for 0.3 mM–30 mM solutions) or 0.3 μCi/100 μl (for 100 mM and 300 mM solutions). 14C12-trehalose was purchased from Hartmann Analytic, Braunschweig (#1249); 14C6-glucose and 14C6-fructose were purchased from Biotrend, Köln (#MC144-50 and 66 #MC1459-50). Six to eight oocytes were transferred into a test tube and washed with oocyte saline. Oocyte saline was removed completely, and 95 μl of the sugar substrate were added for 60 min. After incubation, cells were washed four times with 4 ml ice-cold oocyte saline. Single oocytes were transferred into Pico Prias scintillation vials (Perkin Elmer) and lysed in 200 μl 5% SDS, shaking at approximately 190 rpm for at least 30 min at 20°C–28°C. Three milliliters Rotiszint eco plus scintillation cocktail (Carl Roth) was added to each vial, and scintillation was measured using the Tri-Carb 2810TR scintillation counter (Perkin Elmer). Scintillation of 10 μl sugar substrate of each concentration with 200 μl 5% SDS and 3 ml Rotiszint eco plus scintillation cocktail served as a standard.

Substrate flux was calculated from the measured scintillation according to the respective standard measurements. For statistical analysis, the medium flux and standard error were calculated for oocytes expressing transport proteins and native oocytes and compared using a one-sided t-test or the Mann–Whitney rank test for analysis of non-uniformly distributed samples. Determination of the net-flux was performed by subtracting the medium flux of native oocytes from one test series from each measurement of the same test series and calculating the medium flux and standard error.

Data availability

The full imaging raw data is available at https://dx.doi.org/10.17879/37089751811.

The following data sets were generated
    1. Hertenstein H
    2. McMullen E
    3. Weiler A
    4. Volkenhoff A
    5. Becker HM
    6. Schirmeier S
    (2021) Miami
    Starvation-induced regulation of carbohydrate transport at the blood-brain barrier is TGF-β-signaling dependent.
    https://doi.org/10.17879/37089751811

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    Haemolymph sugar levels in foraging honeybees (Apis mellifera carnica): dependence on metabolic rate and in vivo measurement of maximal rates of trehalose synthesis
    The Journal of Experimental Biology 204:2709–2716.
    1. Koepsell H
    (2020) Glucose transporters in brain in health and disease
    Pflügers Archiv - European Journal of Physiology 472:1299–1343.
    https://doi.org/10.1007/s00424-020-02441-x
  2. Book
    1. Lindsley DL
    2. Zimm GG
    (1992)
    The Genome of Drosophila melanogaster
    Amsterdam, Netherlands: Elsevier Science.

Decision letter

  1. K VijayRaghavan
    Senior and Reviewing Editor; National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

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

Acceptance summary:

The brain is protected from nutrient deprivation. Here, the authors investigate the possible mechanism by which this protection might occur. They make a case for starvation resulting in the release of the transforming growth factor pathway ligand. This activates an arm of the pathway in the perineurial glia, which acts as a blood-brain barrier in flies. This in turn results in the transcriptional upregulation of a carbohydrate transporter. This transporter is capable of transporting glucose and that its capacity to do so enhances upon starvation. They postulate that this is the mechanism by which the brain might be protected from nutrient deprivation.

Decision letter after peer review:

Thank you for submitting your article "Starvation-induced regulation of carbohydrate transport at the blood-brain barrier is TGF-β-signaling dependent" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by K VijayRaghavan as the Senior Editor and Reviewing Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

This paper addresses the interesting question of how the brain reacts differently to nutrient deprivation as compared to the periphery, variously referred to as brain sparing or the self brain hypothesis by some researchers. Using Drosophila larvae, the paper shows that the gene Tret1-1 is transcriptionally upregulated in perineurial BBB cells upon sugar starvation, the gene product is localized in vesicles that is used to transport it to the membrane in a Rab dependent manner. The gene product can transport glucose in Xenopus oocyte system and upregulation of the gene through starvation results in increased transport of glucose in the brain, as shown by in vivo glucose sensor. In the second phase of the paper, they show that this starvation induced upregulation of Tret1-1 is not dependent on insulin, akh, or Alk signaling, but rather by a specific branch of TGFb signaling, namely the one driven by the ligand Gbb.

The strength of the paper is the admirable usage of different techniques to get at a specific issue at a deep resolution, from molecular genetics to biochemistry to neuronal imaging. A potential disadvantage is how rigorous one can or should go in any one of these areas.

Both the reviewers outline some points meant not as strict requirements, but rather for consideration for going a bit deeper. As you can see, most of their points overlap. It will be valuable if the manuscript is revised taking their views into consideration/

Reviewer 1:

1. If you downregulate Tret1-1, do you eliminate glucose uptake increase upon starvation? What´s the phenotype in terms of being more or less resistant to starvation?

2. They test insulin, akh and Alk signaling and show these are not involved. I´m just curious why they have not tested/shown TOR (target of rapamycin). I realize there are many signaling pathways to test, but this was such an obvious candidate in terms of nutrient signaling, especially based on studies on yeast where TOR is involved in putting different types of nutrient transporters to the cell surface.

3. What is known about Gbb expression? The manuscript is unclear on this. They overexpress Gbb in BBB (both peri and subperineurial glia), and they say that "moderate levels of Gbb are produced by an unknown source probably locally in the subperineurial glial cells" (page 13, lines 388-389). Is Gbb expressed in subperineurial glia? Is it upregulated upon starvation?

4. It would be good if they could also show, as an internal control, that some aspect of the above signaling events in the periphery is different than in the brain, e.g. some other sugar transporter or signaling components being downregulated in peripheral tissue upon starvation.

Reviewer 2:

The central case of this story is that the increase in Tret-1 expression is what protects the brain from conditions of starvation. In the manuscript, the evidence to suggest this is indirect. I expected that the authors would have shown the following:

1. In the absence of Tret-1, there is a lack of (or an attenuation in) the protection of the brain from the starved condition. How they assay the protection of the brain could be via size of the brain, reactivation of NBs, or any other means they thought robust and sensitive.

2. In the same condition – absence of Tret-1 and in conditions of starvation – that there is an attenuation of a lack of Glucose transport as measured by the glucose sensor in the blood brain barrier.

The authors seem to suggest that in the starved condition not only does Tret-1 transcription increase, but it also gets re-localized from intracellular vesicles to the plasma membrane. The subcellular localization is interesting because I presume for Tret-1 to act as a transporter of glucose it must localize to the membrane. However, this point is not addressed in the rest of the story (I am not suggesting this as a necessary experiment), and the altered localization was not obvious to me. Could the authors quantify the localisation changes in some manner? And maybe discuss how they think starvation might result in the relocalisation? Or is it possible that membrane localization is present in both conditions, but the increased levels of Tret-1 in the starved condition just shows membrane localization more clearly?

Was there a reason why the authors did not do a quantitative PCR to determine transcriptional changes in tret-1 in response to starvation? Instead, they use a reporter-based assay for this. They do show a Western in figure 3, but I am concerned that the level of tubulin are very different in the fed and starved conditions. Particularly because in 3B they use a ratiometric quantification to show enhanced levels of the protein, the ratiometric quantification will show an exaggerated difference in the starved condition if the tubulin levels are low.

https://doi.org/10.7554/eLife.62503.sa1

Author response

Reviewer 1:

1. If you downregulate Tret1-1, do you eliminate glucose uptake increase upon starvation?

To answer this question, we expressed Tret1-1dsRNA in glial cells and measured glucose uptake into the brains of those animals under standard conditions and upon starvation. Tret1-1 knockdown abolishes the increase of glucose uptake upon starvation. We added this data to the manuscript (Figure 5 and corresponding text). The glucose uptake under fed conditions increases slightly upon Tret1-1 knockdown. This effect is most likely caused by overcompensation via other sugar transporters that are expressed in the BBB (McMullen et al., 2021). It seems however that such compensation cannot rescue glucose uptake in starved animals. This increase in glucose uptake, thus, is specifically caused by an increased expression of Tret1-1.

What´s the phenotype in terms of being more or less resistant to starvation?

We are sorry for being unclear about this. Animals which are completely starved after an age of 70 hours (25 °C) do not grow anymore but nevertheless survive and give rise to adults. Therefore, we start starving larvae approx. 14 hours before this developmental timepoint, since this period is critical for development. Wild type animals can survive starvation for 40 h at this stage (see also new scheme in Figure 1), although they do not grow during this period and just start growing again if refed. If the starvation is prolonged, the animals die. Animals that are starvation susceptible, like jeb knockdown larvae, do not survive this starvation paradigm, a phenotype that we termed “starvation susceptibility”. We explained this better in the text now.

2. They test insulin, akh and Alk signaling and show these are not involved. I´m just curious why they have not tested/shown TOR (target of rapamycin). I realize there are many signaling pathways to test, but this was such an obvious candidate in terms of nutrient signaling, especially based on studies on yeast where TOR is involved in putting different types of nutrient transporters to the cell surface.

Thank you for this suggestion. In the current study we aimed to analyze how Tret1-1 upregulation upon starvation is regulated, since we found that this occurs via TGF-β signaling, we did not test all other pathways that could potentially be involved any more.

Signaling via TOR is indeed an obvious candidate. Thus, to answer the question we knocked down TOR using two different dsRNA constructs. We did not see any impairment of Tret1-1 upregulation in such animals, indicating that TOR is not involved in Tret1-1 regulation. See Author response image 1. Since the result was negative, we did not include the data in the manuscript.

Author response image 1
Tret1-1 upregulation upon starvation is independent of TOR signaling.

Quantified is the ratio of Tret1-1 fluorescence intensities in starved larval VNCs vs. VNCs of fed animals. Knockdown of TOR expressing using either TOR33951 or TOR35578 in glial cells shows a comparable upregulation of Tret1-1 to the control. N=5 n >9.

3. What is known about Gbb expression? The manuscript is unclear on this. They overexpress Gbb in BBB (both peri and subperineurial glia), and they say that "moderate levels of Gbb are produced by an unknown source probably locally in the subperineurial glial cells" (page 13, lines 388-389). Is Gbb expressed in subperineurial glia? Is it upregulated upon starvation?

There is an antibody against Gbb available that was previously used to stain Gbb in NMJs (Akiyama et al., 2012; James et al., 2014). We used this antibody now to stain brains for Gbb. The staining is weak, but specific. Gbb seems to be expressed in all cell types of the nervous system. Upon starvation Gbb is upregulated in the brain. We included this data into the manuscript (Figure 8 and corresponding text).

Further attempts to identify the cell type that is crucial for Tret1-1 induction upon starvation failed unfortunately. We overexpressed Gbb in different glial cell types (also just SPGs or just PGs), but unfortunately these experiments led to (semi-)lethality of the animals. This phenotype is most likely caused by developmental problems caused by the overexpression of Gbb in the brain or other tissues. Gbb is important during development. The used Gal4 driver lines also show expression in other cell types outside the central nervous system and also early in development. This additional expression most likely causes the (semi)-lethality and thus does not allow analyses of the effect of glial subtype specific overexpression of Gbb.

Next, we attempted to identify the cell type from which Gbb was secreted using Gbb knockdown (HMS01243) in either perineurial or subperineurial glial cells. However, knockdown of Gbb in these cell types did not change Tret1-1 upregulation upon starvation. This most likely means that the signal that induces Tret1-1 upregulation does not originate from a single cell type, which would go along with the expression and starvation-induced induction of Gbb in several glial cell types. Alternatively, different cell types could compensate for the loss of Gbb signal from one cell type. We were unfortunately not able to test a panglial knockdown of Gbb due to restricted access to the lab. Since these results unfortunately still do not answer the question where the signal comes from, we did not include them in the manuscript.

4. It would be good if they could also show, as an internal control, that some aspect of the above signaling events in the periphery is different than in the brain, e.g. some other sugar transporter or signaling components being downregulated in peripheral tissue upon starvation.

Attempts to study Tret1-1 expression in muscle upon starvation did not give coherent results. Due to the very thick tissue of the muscles and the extremely big cells, the fluorescence intensities of Tret1-1 vary a lot within a Z-stack. Analyzing and comparing the intensity of Tret1-1 staining in between animals and in between animals with different genetic backgrounds was therefore not possible. Further attempts to study Tret1-1 regulation in peripheral tissues were impossible due to the restricted access to the lab, that forced us to prioritize certain experiments over others. In Drosophila, hardly anything is known about the expression of other sugar transporters in the periphery. Thus, analyzing the expression patterns of other putative sugar transporters and their regulation in the periphery upon starvation would be a big endeavor and was unfortunately not possible within the timeframe of this revision.

Reviewer 2:

The central case of this story is that the increase in Tret-1 expression is what protects the brain from conditions of starvation. In the manuscript, the evidence to suggest this is indirect. I expected that the authors would have shown the following:

1. In the absence of Tret-1, there is a lack of (or an attenuation in) the protection of the brain from the starved condition. How they assay the protection of the brain could be via size of the brain, reactivation of NBs, or any other means they thought robust and sensitive.

Thank you for this suggestion. We tried to measure the size of the brains of starved wild type and Tret1-1- knockdown animals. We did this using comparable confocal slices of each brain and measuring the area of the brain (2D) in those slices. When doing this the difference between control brains and Tret1-1 knockdown brains is not significant, even though there is a tendency towards being smaller in Tret1-1 knockdown brains. To analyze brain differences in brain volume (3D), which most likely will show a bigger difference, we would need many additional scans of starved brains for both genotypes. Due to restricted access to the lab, we were unfortunately not able to conduct those additional experiments. These pandemic-induced restrictions unfortunately also prevented us from analyzing NB reactivation.

2. In the same condition – absence of Tret-1 and in conditions of starvation – that there is an attenuation of a lack of Glucose transport as measured by the glucose sensor in the blood brain barrier.

To answer this question, that was also raised by reviewer I, we expressed Tret1-1dsRNA in glial cells and measured glucose uptake into the brains of those animals under standard conditions and upon starvation. Tret1-1 knockdown abolishes the increase of glucose uptake upon starvation. We added this data to the manuscript (Figure 5 and corresponding text). The glucose uptake under fed conditions increases slightly upon Tret1-1 knockdown. This effect is most likely caused by overcompensation via other sugar transporters that are expressed in the BBB (McMullen et al., 2021). It seems however that such compensation cannot rescue glucose uptake in starved animals. This increase in glucose uptake, thus, is specifically caused by an increased expression of Tret1-1.

The authors seem to suggest that in the starved condition not only does Tret-1 transcription increase, but it also gets re-localized from intracellular vesicles to the plasma membrane. The subcellular localization is interesting because I presume for Tret-1 to act as a transporter of glucose it must localize to the membrane. However, this point is not addressed in the rest of the story (I am not suggesting this as a necessary experiment), and the altered localization was not obvious to me. Could the authors quantify the localisation changes in some manner? And maybe discuss how they think starvation might result in the relocalisation? Or is it possible that membrane localization is present in both conditions, but the increased levels of Tret-1 in the starved condition just shows membrane localization more clearly?

Thank you for this remark. Several attempts (TIRF microscopy, expansion microscopy) were performed to analyze a change in Tret1-1 localization upon starvation in more detail. The small size of perineurial glia make this analysis very difficult. Mammalian GLUT4 is stored in storage vesicles in the cytoplasm of adipose cells. Upon increased insulin levels these vesicles are recruited towards the membrane and GLUT4 is mostly localized at the membrane (Klip et al., 2019). Tret1-1 upregulation upon starvation is independent of insulin signaling, however. The general increase of Tret1-1 expression upon starvation might indirectly increase the amount of Tret1-1 at the plasma membrane independently of a relocation. Thus, we cannot exclude that under starvation conditions the same portion of Tret1-1 protein localizes to the plasma membrane as under normal fed conditions. Tret1-1 colocalization with Rab GTPases, however, might suggest a similar translocation as seen for mGLUT4. We rephrased this part in the manuscript and discussion to account for the hypothetical character of the translocation idea.

Was there a reason why the authors did not do a quantitative PCR to determine transcriptional changes in tret-1 in response to starvation? Instead, they use a reporter-based assay for this. They do show a Western in figure 3, but I am concerned that the level of tubulin are very different in the fed and starved conditions. Particularly because in 3B they use a ratiometric quantification to show enhanced levels of the protein, the ratiometric quantification will show an exaggerated difference in the starved condition if the tubulin levels are low.

Quantitative PCR is a very delicate technique to analyze transcriptional changes. Tret1-1 is specifically expressed in perineurial glia that represents a very small number of cells in the brain. Therefore, it is not trivial to detect Tret1-1 mRNA quantitatively in the mRNA of brain samples. Since this approach would likely have required a lot of optimization, we decided to use another approach. We agree, however, that our western blots might not be optimal. Thus, we now added another analysis to verify the results of the western blots. We quantified stgGFP (in Tret1-1>stgGFP animals) in individual nuclei and normalized it to DAPI, since it seems very unlikely that the DNA content of a cell would change upon starvation. This technique is still ratiometric, but both independent approaches show that Tret1-1 is upregulated on a transcriptional level. Thus, we are now very confident that our observation is true. We included this data in Figure 3 and the corresponding text.

https://doi.org/10.7554/eLife.62503.sa2

Article and author information

Author details

  1. Helen Hertenstein

    Department of Biology, Institute of Zoology, Technische Universität Dresden, Dresden, Germany
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
  2. Ellen McMullen

    Institut für Neuro- und Verhaltensbiologie, WWU Münster, Münster, Germany
    Contribution
    Formal analysis, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  3. Astrid Weiler

    Department of Biology, Institute of Zoology, Technische Universität Dresden, Dresden, Germany
    Contribution
    Formal analysis, Investigation, Visualization
    Competing interests
    No competing interests declared
  4. Anne Volkenhoff

    Department of Biology, Institute of Zoology, Technische Universität Dresden, Dresden, Germany
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  5. Holger M Becker

    1. Department of Biology, Institute of Zoology, Technische Universität Dresden, Dresden, Germany
    2. Division of General Zoology, Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany
    Contribution
    Conceptualization, Formal analysis, Supervision, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2700-6117
  6. Stefanie Schirmeier

    Department of Biology, Institute of Zoology, Technische Universität Dresden, Dresden, Germany
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    stefanie.schirmeier@tu-dresden.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8431-9593

Funding

Deutsche Forschungsgemeinschaft (SFB1009)

  • Stefanie Schirmeier

Deutsche Forschungsgemeinschaft (SCHI 1380/2-1)

  • Stefanie Schirmeier

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

Acknowledgements

We are grateful to M Brankatschk for fly stocks. We thank Astrid Fleige for help with cloning and western blots. We are grateful to C Klämbt for discussions and critical reading of the manuscript. The work was supported by grants of the DFG to SS (SFB1009, SCHI 1380/2–1).

Senior and Reviewing Editor

  1. K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

Publication history

  1. Received: August 26, 2020
  2. Accepted: April 13, 2021
  3. Version of Record published: May 25, 2021 (version 1)

Copyright

© 2021, Hertenstein 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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