Macrophage‐derived insulin antagonist ImpL2 induces lipoprotein mobilization upon bacterial infection

To elicit an immune response, adult fruit flies (Drosophila melanogaster) were injected with 20,000 extracellular bacteria (Streptococcus pneumoniae). In our experimental model, acute streptococcal infection leads to rapid activation of macrophages, called plasmatocytes in Drosophila, and their pro‐inflammatory polarization (Bajgar & Dolezal, 2018; Krejčová et al, 2019). The infection culminates during the first 24 h of infection, which determines whether or not an individual survives the infection. Although all pathogenic bacteria in surviving flies are eliminated within the first 5 days, the flies continue to decline due to the long‐term effects of the infection experienced (Bajgar & Dolezal, 2018; Krejčová et al, 2019). This treatment offers a standardized course of immune response in which macrophage pro‐inflammatory polarization and their bactericidal activity is crucial for limiting the bacterial burden (Bajgar & Dolezal, 2018). To determine how the ongoing immune response is reflected by rearrangement of the systemic metabolism, we analyzed metabolic changes in infected individuals 24 h post‐infection (hpi).

We found that the acute phase of infection is accompanied by a depletion of two major storage molecules, glycogen (GLY) and triglycerides (TG) when measured on the whole‐individual level (Fig 1A). This is consistent with the pattern observed in the fat body, organ comprising the functionalities of mammalian liver and adipose tissue. In this tissue, the levels of all analyzed carbohydrates and lipids are significantly reduced upon infection (Fig 1B). Depletion of lipid stores is further documented by a significantly decreased diameter of lipid droplets and the area they occupy in adipocytes of infected flies (Fig 1C) as quantified from the confocal images of the fat body stained for neutral lipids (Fig 1D).

Examination of the fat body lipid content using lipidomic analysis revealed that depletion of lipid stores in this organ is accompanied by a significant shift in lipid composition. While the main storage lipids, triglycerides, prevail in the fat body of control flies, their relative amounts decrease significantly after infection in favor of polar lipids (phosphatidylcholine, PC; phosphatidylethanolamine, PE) and diglycerides (DG; Figs 1E and EV1A), a transport form of lipids in insects (Palm et al, 2012).

Contrary to that, the titer of carbohydrates and lipids rises significantly in circulation upon infection (Fig 1F). These observations imply that the infection is accompanied by depletion of energy stores and redistribution of nutrients between tissues via circulation. To investigate whether mobilized nutrients serve as metabolic support for the activated immune system, we analyzed the metabolic profile of macrophages at 24 hpi. Macrophages isolated from infected individuals display elevated levels of all analyzed carbohydrates and lipids when compared to uninfected controls (Fig 1G).

Lipidomic analysis revealed that the overall lipid content is 3.5‐fold increased in infection‐activated macrophages compared to controls (Fig EV1B). Moreover, the infection affects the lipid composition in these cells displaying a significantly enhanced fraction of hydrolyzed forms of polar lipids (lysophosphatidylcholine, LPC; lysophosphatidylethanolamine, LPE; Figs 1H and EV1C) that may be attributed to increased endocytosis of circulating lipoproteins and eicosanoid production (Lee et al, 2020; Liu et al, 2020).

To further characterize the infection‐induced redistribution of lipids from the fat body to macrophages, we fed flies with a mixture of ¹³C‐labeled free fatty acids (¹³C‐FFAs) and monitored their immediate incorporation into tissues. While in control subjects, most of the ¹³C‐FFAs are destined for the fat body, and only a small fraction incorporates into macrophages, this ratio is completely reversed upon infection (Fig 1I). Since the control and infected flies display comparable dietary intake, the possibility that the observed differences may be accounted to infection‐induced anorexia can be excluded (Fig EV1D). Overall, our data show that infection is accompanied by a rearrangement of systemic metabolism that leads to a redistribution of lipids from the central metabolic organ toward the circulation and the activated immune system. To explore the possibility that the observed metabolic changes are induced by signaling factors originating from macrophages, we proceeded to a detailed analysis of these cells after infection (Fig 1J).

To better understand the ongoing processes in infection‐activated macrophages, we performed a comparative analysis of their transcriptomic profile at 24 hpi. Gene set enrichment analysis revealed that along with the activation of immune‐related processes, macrophages undergo remarkable changes in their cellular metabolism (Figs 2A and EV2A). Infection‐activated macrophages attenuate the expression of genes involved in the mitochondrial generation of ATP and simultaneously enhance the expression of genes involved in the regulation of lipid and cholesterol metabolism (Fig 2A). These data further extend our previous observations that bactericidal polarization of Drosophila macrophages is coupled with the remodeling of their cellular metabolism toward aerobic glycolysis (Krejčová et al, 2019). We have previously shown that the adoption of aerobic glycolysis by Drosophila macrophages is fundamental for their bactericidal function and that this metabolic remodeling is analogical to mammalian macrophages governed by the master regulator Hif1α, which controls the expression of many metabolic genes (Galvan‐Pena & O'Neill, 2014; Krejčová et al, 2019).

We further identified several signaling factors whose induction goes hand in hand with infection‐induced macrophage polarization (Fig 2B). From several candidates, we chose ImpL2 for further investigation since it is highly expressed in macrophages, displays the most significant increase in response to infection (Figs 2C and EV2B), and has been previously shown to have a potential to affect systemic lipid metabolism (Kwon et al, 2015). Other potential candidates, the signaling factors Unpaired 3 (Upd3) and Eiger (Egr) were tested together with ImpL2, but already the initial experiments showed that neither Upd3 nor Egr had a rather negligible effect on lipid mobilization from the fat body during infection (Appendix Figs S1–S6).

To investigate the spatial pattern of ImpL2 expression, we employed a fly strain bearing a fluorescent ImpL2 reporter (ImpL2‐Gal4 > UASmCherry). We found that ImpL2 promoter activity is almost exclusive to macrophages, as evidenced by the strong production of the ImpL2‐mCherry signal in cells positive for the Drosophila macrophage marker NimC1 (Fig 2D and Appendix Fig S7).

Next, we investigated the mechanism controlling ImpL2 expression in these cells. Given that HIF1α is the master regulator of macrophage metabolic remodeling during infection, we assessed its effect on ImpL2 expression. Macrophage‐specific knockdown of Hif1α (Crq > Gal4; UAS‐GFP, Hif1α^RNAi) abolished the infection‐induced increase in ImpL2 expression in these cells (Fig 2E; see Fig EV2C for Hif1α^RNAi efficiency; see Fig EV2D for genotype explanations). This interaction is further confirmed by the direct binding of HIF1α to the ImpL2 promoter, as revealed by Chip‐qPCR analysis (Fig 2F).

Taken together, the presented data show that metabolic rearrangement of pro‐inflammatory macrophages is coupled to ImpL2 expression since both processes are governed by the same transcription factor, HIF1α. This implies a possible role of ImpL2 as a signal produced by pro‐inflammatory macrophages in reflection of their newly adopted metabolic program associated with specific nutritional demands (Fig 2G).

To investigate the effect of macrophage‐derived IMPL2 on the redistribution of lipids during infection, we generated flies carrying genetic constructs for time‐limited macrophage‐specific ImpL2 knockdown (Mφ‐ImpL2^RNAi) or overexpression (Mφ‐ImpL2^CDS). Using these fly strains, we experimentally manipulated ImpL2 expression macrophage‐specifically 24 h before the infection and compared the effect of these interventions to control lines of the respective genetic background (TRiP^control, W^control; see Fig EV2D for an explanation of the genotypes and Fig EV3A for efficiency of macrophages‐specific ImpL2 manipulations).

First, we evaluated the impact of Mφ‐ImpL2 manipulations on the morphology of the fat body. While flies of the control genotypes (TRiP^control, W^control) display the characteristic infection‐induced changes in the morphology of lipid droplets in adipocytes, Mφ‐ImpL2^RNAi abrogates these changes. Accordingly, macrophage‐specific overexpression of ImpL2 (Mφ‐ImpL2^CDS) is sufficient to mimic the infection‐induced changes even under control conditions (Figs 3A and EV3B and C). These morphological changes can be attributed to the redistribution of lipids from the fat body to the circulation, as evidenced by triglyceride, cholesterol, and cholesteryl‐ester levels, which are decreased in the fat body and elevated in circulation upon infection. Since all these metabolites show an identical pattern in response to treatments and genetic manipulations, they are displayed in the main Figures as “Lipids” for simplicity and presented individually in the Expanded View file (Fig EV3D–F).

While Mφ‐ImpL2^RNAi prevents the infection‐induced depletion of lipids in the fat body and their subsequent rise in circulation, these changes are invoked by mere Mφ‐ImpL2^CDS even without infection (Figs 3B and C, and EV3D–F).

Fat body lipidomics provides further indications that macrophage‐derived IMPL2 plays a central role in the mobilization of lipids upon infection. Mφ‐ImpL2^RNAi suppresses the characteristic infection‐induced changes in the proportion of lipid species in the fat body as manifested by increased abundance of PC, PE, and DG, whereas enrichment of these lipid classes can be observed in the fat body of flies carrying Mφ‐ImpL2^CDS even under control conditions (Fig 3D and E).

To comprehend the mechanism of the ImpL2‐induced changes in the fat body, we measured the expression pattern of genes involved in lipolysis (brummer, bmm; Hormone‐sensitive lipase, Hsl) and the production of lipoproteins (Apolipoprotein lipid transfer particle, Apoltp; apolipophorin, apolpp; Neuropeptide‐like precursor 2, Nplp2; Microsomal triacylglycerol transfer protein, Mtp). Expression of all these genes is significantly elevated in the fat body upon infection, and the expression pattern of bmm, Apoltp, apolpp, and Mtp seems to be dependent on macrophage‐derived ImpL2 (Figs 3F and EV4A). Interestingly, all these genes are known FOXO targets (Brankatschk et al, 2014), which implicates the involvement of this transcription factor in the mediation of IMPL2 effects. This notion is supported by the expression of two commonly used FOXO readouts (Thor, 4EBP; eukaryotic translation initiation factor 4E1, eIF4E1; Santalla et al, 2022), showing analogous expression patterns with respect to infection and Mφ‐ImpL2 manipulations (Fig 3F). Consistent with metabolic effects attributed to Mφ‐ImpL2 manipulations, identical metabolic effect has been achieved also by using an alternative ImpL2^RNAi fly line (Appendix Figs S16–S18). Infection also leads to increased expression of Hsl and the exchange lipoprotein Nplp2 in the fat body, however, their expression is not affected by Mφ‐ImpL2 manipulations, suggesting an alternative mechanism for their regulation.

To determine whether FOXO plays a role in the manifestation of IMPL2 effects in the fat body, we decided to analyze its subcellular localization and its contribution to the infection‐induced changes in lipid droplet morphology. While FOXO may be found distributed evenly between the nucleus and cytosol under normal physiological conditions, it becomes predominantly nuclear in response to metabolic stress (Koyama et al, 2014). This translocation also occurs during bacterial infection; however, it is impaired by Mφ‐ImpL2^RNAi and can be induced by Mφ‐ImpL2^CDS even in uninfected individuals (Figs 4A and EV5A). Moreover, flies carrying the hypomorphic foxo allele together with Mφ‐ImpL2^CDS do not exhibit lipid depletion observed otherwise in Mφ‐ImpL2^CDS flies, as documented by lipid droplet morphology in adipocytes (Fig 4B–D). In conclusion, the effects of macrophage‐derived IMPL2 on lipid metabolism in the fat body are mediated by the transcription factor FOXO, which is required for the mobilization of lipid stores upon infection.

Given that FOXO nuclear translocation is controlled by PI3K activity in situations of metabolic stress (Zhao et al, 2021), we analyzed the effect of Mφ‐ImpL2 manipulations on PI3K activity in the fat body. For this purpose, we employed a fly strain carrying in vivo PI3K reporter based on pleckstrin homology domain fused with GFP (tGPH; Britton et al, 2002). The signal, which is predominately localized to the plasma membrane in control flies, becomes more cytosolic in infected individuals, documenting decreased PI3K signaling in the fat body of infected flies. Since Mφ‐ImpL2^CDS phenocopies tGPH localization during infection even under control conditions (Fig 5A and B), we postulate that macrophage‐derived ImpL2 silences PI3K enzymatic activity in the fat body upon infection.

The impact of macrophage‐derived ImpL2 on FOXO and PI3K activity in the fat body indicates that the ImpL2 effects may be mediated via silencing of insulin signaling since both these factors play a central role in insulin signaling in Drosophila (DiAngelo et al, 2009). This is consistent with the previously described function of ImpL2 as an insulin signaling antagonist with a high affinity to circulating insulin and Drosophila insulin‐like peptides (Honegger et al, 2008; Kwon et al, 2015).

Therefore, we aim to investigate the effects of insulin signaling on the redistribution of lipid stores upon infection. For this purpose, we generated flies with constitutively active (FB > InR^CA) or genetically abrogated (FB > InR^DN and FB > PTEN^CDS) insulin signaling exclusively in the fat body by using a fat body‐specific Gal4 driver (FB‐Gal4; Grönke et al, 2003; see Fig EV2D for genotype explanations). While mere silencing of insulin signaling in the fat body of uninfected flies (FB > InR^DN and FB > PTEN^CDS) results in the depletion of lipid stores in this organ and their accumulation in the circulation, constitutive activation of insulin receptor (FB > InR^CA) does not allow for the redistribution of lipids between these two compartments otherwise observed upon infection (Fig 5C and D and Appendix Fig S8A and B). In concordance with the previously observed morphology of lipid droplets in the fat body, the flies bearing the foxo hypomorphic allele (foxo^hypo.) were not able to induce mobilization of lipids from the fat body into the circulation upon infection as well as flies with foxo hypomorphic allele and macrophage‐specific overexpression of ImpL2 (Hml > ImpL2^CDS; foxo^hypo.; Fig 5C and D and Appendix Fig S8A and B). These data further support our conclusion that the metabolic effects of ImpL2 are mediated by the activation of the FOXO transcriptional program.

Moreover, manipulation of insulin signaling in the fat body also affects the expression of genes involved in the assembly and mobilization of lipoproteins (Apoltp, apolpp, Mtp) in this tissue, which has been demonstrated above to respond to Mφ‐ImpL2 manipulations (Fig 5E and Appendix Fig S8C).

As anticipated, fat body‐specific knockdown of genes involved in the assembly and mobilization of lipoproteins (Apoltp, apolpp, Mtp; see Appendix Fig S8D for RNAi efficiency and Fig EV2D for genotype descriptions) intervenes with the infection‐induced depletion of lipid stores in the fat body and their mobilization into circulation (Fig 5F and G and Appendix Fig S9A and B).

Although the epistatic effect of macrophage‐derived IMPL2 on insulin signaling in the fat body has not been explicitly demonstrated here, the data suggest that the effect of IMPL2 on the mobilization of lipid stores is likely mediated by attenuation of insulin signaling in the fat body, leading to increased production of lipoproteins into the circulation via a FOXO‐induced transcriptional program (Fig 5H).

To address the question of whether ImpL2‐induced lipoprotein mobilization is required for the redistribution of lipids toward infection‐activated macrophages (Fig 1G and I), we assessed the incorporation of dietary ¹³C‐FFAs and macrophage lipid content in flies with Mφ‐ImpL2 manipulations (see Appendix Fig S19 for experimental setup).

While infection in flies of control genotypes leads to the enhanced ¹³C‐FFAs accumulation in activated macrophages at the expense of the fat body, this effect is diminished significantly in flies with Mφ‐ImpL2^RNAi. Contrary to that, mere Mφ‐ImpL2^CDS leads to enhanced ¹³C‐FFAs levels in macrophages in both infected and control flies (Fig 6A). Notably, we have not observed any marks of infection‐induced anorexia as documented by comparable dietary uptake in flies regardless of treatment or their genotypes (Appendix Fig S10A).

That is consistent with elevated lipid content in macrophages of infected flies of control genotypes, which is not present in flies with Mφ‐ImpL2^RNAi but can be induced in uninfected flies by Mφ‐ImpL2^CDS (Fig 6B and Appendix Fig S10B). These data imply that macrophage‐derived ImpL2 is required for enhanced availability of lipids for the immune system and their accumulation in activated macrophages.

Further, we evaluated the importance of IMPL2‐induced metabolic changes for immune function and resistance to infection. In this regard, we assessed the survival rate of flies with manipulated IMPL2 production in macrophages and flies with knockdown of genes required for the assembly and production of lipoproteins from the fat body.

Mφ‐ImpL2^RNAi leads to a significantly reduced phagocytic capacity of macrophages as documented by the decreased number of phagocytic events upon injection of a phagocytic marker (pHrodo‐S. aureus; Fig 6C and D). In line with that, Mφ‐ImpL2^RNAi leads to increased pathogen load in these flies and decreased survival of infection, whereas flies with Mφ‐ImpL2^CDS display lower pathogen load and improved infection resistance (Fig 6E and F and Appendix Fig S10C). Cell‐autonomous effects of Mφ‐Imp2 manipulations on the function of these cells were found to be insignificant since macrophages isolated from these flies show normal production of antimicrobial peptides, markers of metabolic polarization, and macrophage numbers (Appendix Figs S11–S15).

The importance of enhanced mobilization of lipoproteins during infection is documented by the decreased survival rate of flies with the fat body‐specific knockdown of genes involved in lipoprotein assembly (Apoltp, apolpp, Mtp; Fig 7A and Appendix Fig S10D). Inhibition of mobilization of lipoproteins by fat body‐specific knockdown of apolpp leads to decreased phagocytic capability of macrophages resulting in enhanced pathogen load in these flies at 24 hpi (Fig 7B–D). This is in concordance with enhanced lipoprotein uptake by infection‐activated macrophages compared to uninfected controls, as documented by the number of endocytic events of pHrodo‐labeled low‐density lipoproteins (LDL; Fig 7E and F), the enhanced proportion of macrophages containing lipid droplets in their cytosol as well as by accumulation of fluorescently‐labeled FFAs (Appendix Figs S20 and S21). Increased uptake of lipids by activated macrophages and their subsequent processing is further supported by enhanced expression of genes involved in these processes (Appendix Figs S22 and S23).

The presented data demonstrate that the pro‐inflammatory polarization of Drosophila macrophages is associated with the production of the signaling factor IMPL2 through the activity of the transcription factor HIF1α. IMPL2 subsequently triggers the mobilization of lipoproteins in the fat body to nutritionally supplement the immune system.

To investigate whether an analogous mechanism may be evolutionarily conserved and relevant in mammals, we focused on mammalian ImpL2 homolog Insulin growth factor binding protein 7 (Igfbp7; Honegger et al, 2008). Igfbp7 is a member of insulin growth factors with high affinity to human insulin and its functional and sequence homology to ImpL2 has been described previously (Sloth Andersen et al, 2000; Roed et al, 2018).

First, we analyzed the production of IGFBP7 in human monocyte‐derived macrophages (THP1 cells) during their bactericidal polarization. Pro‐inflammatory polarization of THP1 cells induced by administration of S. pneumoniae or LPS leads to significant upregulation of IGFBP7 at both mRNA (Fig 8A) and protein levels (Fig 8B). Moreover, we revealed that IGFBP7 production in THP1 cells is controlled by the transcription factor HIF1α since the application of its inhibitor (KC7F2) or agonist (DMOG) has a major effect on IGFBP7 production in these cells regardless of their activation state (Fig 8A and B). Next, we investigated the effects of bacterial endotoxins (LPS) on IGFBP7 expression in liver macrophages (see Appendix Fig S24A for experimental design). Consistently with the data from THP1 cells, LPS induces IGFBP7 expression in liver macrophages isolated from mice and humans (Fig 8C and D).

To induce gene‐specific knockdown exclusively in murine liver macrophages in vivo, we employed glucan particles as a macrophage‐specific delivery tool that was developed for this purpose (Tencerova, 2020). Intravenously administered glucan particles loaded with siRNA against Igfbp7 are specifically scavenged by liver macrophages and significantly reduce Igfbp7 expression exclusively in these cells (Tencerova et al, 2015; Morgantini et al, 2019). Knockdown of Igfbp7, specifically in murine liver macrophages, results in decreased expression of apolipoprotein genes in hepatocytes in vivo, as revealed by their transcriptomic analysis (Fig 8F and Appendix Fig S24B).

To further test the IGFBP7 potential to induce lipoprotein production in human hepatocytes, we employed an organotypic 3D model of primary human liver cells in which cellular phenotypes closely resemble liver cells at the transcriptomic, proteomic, and metabolomic level in vivo (Bell et al, 2017; Vorrink et al, 2017; Oliva‐Vilarnau et al, 2020). Indeed, the administration of human recombinant IGFBP7 on hepatocellular spheroids leads to elevated LDL and VLDL titers in culture media (Fig 8E).

Overall, our data indicate that Igfbp7 may play an analogous role to Drosophila ImpL2 since it is produced by liver macrophages in response to their pro‐inflammatory polarization in a HIF1α‐dependent manner and that IGFBP7 production by macrophages can elicit the production of lipoproteins from neighboring hepatocytes (Fig 8G).

The flies were raised on a diet containing cornmeal (80 g/l), sucrose (50 g/l), yeast (40 g/l), agar (10 g/l), and 10%‐methylparaben (16.7 ml/l) and maintained in a humidity‐controlled environment with a natural 12 h/12 h light/dark cycle at 25°C. Flies carrying Gal80 protein were raised at 18°C and transferred to 29°C 24 h before infection in order to degrade temperature‐sensitive Gal80. Prior to the experiments, both experimental and control flies were kept in plastic vials on a sucrose‐free cornmeal diet (cornmeal 53.5 g/l, yeast 28.2 g/l, agar 6.2 g/l and 10%‐methylparaben 16.7 ml/l) for 7 days. Flies infected with S. pneumoniae were kept on a sucrose‐free cornmeal diet in incubators at 29°C due to the temperature sensitivity of S. pneumoniae. Infected individuals were transferred to fresh vials every other day without the use of CO₂ to ensure good food conditions.

The Streptococcus pneumoniae strain EJ1 was stored at −80°C in Tryptic Soy Broth (TSB) media containing 10% glycerol. For the experiments, bacteria were streaked onto agar plates containing 3% TSB and 100 mg/ml streptomycin and subsequently incubated at 37°C in 5% CO₂ overnight. Single colonies were inoculated into 3 ml of TSB liquid media with 100 mg/ml of streptomycin and 100,000 units of catalase and incubated at 37°C + 5% CO₂ overnight. Bacterial density was measured after an additional 4 h so that it reached an approximate 0.4 OD600. Final bacterial cultures were centrifuged and dissolved in PBS so the final OD reached 2.4. The S. pneumoniae culture was kept on ice before injection and during the injection itself. Seven‐day‐old males were anesthetized with CO₂ and injected with a 50 nl culture containing 20,000 S. pneumoniae bacteria or 50 nl of mock buffer (PBS) into the ventrolateral side of the abdomen using an Eppendorf Femtojet microinjector.

Streptococcus‐injected flies were kept at 29°C in vials with approximately 30 individuals per vial and were transferred to fresh food every other day. Dead flies were counted daily. At least three independent experiments were performed and combined into a single survival curve generated in GraphPad Prism software; individual experiments showed comparable results. The average number of individuals was more than 500 for each genotype and replicate.

Single flies were homogenized in PBS using a motorized plastic pestle in 1.5 ml tubes. Bacteria were plated in spots onto TSB (S. pneumoniae) agar plates containing streptomycin in serial dilutions and incubated overnight at 37°C before manual counting. Pathogen loads of 16 flies were determined for each genotype and treatment in each experiment; at least three independent infection experiments were conducted and the results were combined into one graph (in all presented cases, individual experiments showed comparable results).

GFP‐labeled macrophages were isolated from Crq > Gal4 UAS‐eGFP male flies using fluorescence‐activated cell sorting (FACS; Krejčová et al, 2019). Approximately 200 flies were anesthetized with CO₂, washed in PBS, and homogenized in 600 ml of PBS using a pestle. The homogenate was sieved through a nylon cell strainer (40 μm). This strainer was then additionally washed with 200 μl of PBS, which was added to the homogenate subsequently. The samples were centrifuged (3 min, 4°C, 3,500 rpm) and the supernatant was washed with ice‐cold PBS after each centrifugation (three times). Before sorting, samples were transferred to FACS polystyrene tubes using a disposable bacterial filter (50 μm, Sysmex) and macrophages were sorted into 100 μl of PBS using an S3™ Cell Sorter (BioRad). Isolated cells were verified by fluorescence microscopy and differential interference contrast. Different numbers of isolated macrophages were used in different subsequent analyses. To this end, different numbers of flies were used for their isolation, specifically 90 flies were used to isolate 20,000 macrophages for qPCR analysis; approximately 160 flies were used to isolate 50,000 macrophages for metabolic analysis; approximately 300 flies were used to isolate 100,000 and 200,000 macrophages for lipidomic and transcriptomic analyses.

Gene expression analyses were performed on several types of samples: six whole flies, six thoraxes, six fat bodies, or 20,000 isolated macrophages. For a description of the dissection procedure see Appendix Fig S25. Macrophages were isolated by a cell sorter (S3e Cell Sorter, BioRad) as described previously (Krejčová et al, 2019) while dissections were made in PBS, transferred to TRIzol Reagent (Invitrogen), and homogenized using a DEPC‐treated pestle. Subsequently, RNA was extracted by TRIzol Reagent (Invitrogen) according to the manufacturer's protocol. Superscript III Reverse Transcriptase (Invitrogen) primed by oligo(dT)20 primer was used for reverse transcription. Relative expression rates for particular genes were quantified on a 384CFX 1000 Touch Real‐Time Cycler (BioRad) using the TP 2x SYBR Master Mix (Top‐Bio) in three technical replicates with the following protocol: initial denaturation—3 min at 95°C, amplification—15 s at 94°C, 20 s at 56°C, 25 s at 72°C for 40 cycles. Melting curve analysis was performed at 65–85°C/step 0.5°C. The primer sequences are listed in the Key Resources Table. The qPCR data were analyzed using double delta Ct analysis, and the expressions or specific genes were normalized to the expression of Ribosomal protein 49 (Rp49) in the corresponding sample. The relative values (fold change) to control are shown in the graphs.

To measure metabolite concentration, isolated macrophages, whole flies, fat bodies, or hemolymph (circulation) were used. Hemolymph was isolated from 25 adult males by centrifugation (14,000 rpm, 5 min) through a silica‐gel filter into 50 μl of PBS. For measurement of metabolites from whole flies, five flies were homogenized in 200 μl of PBS and centrifuged (3 min, 4°C, 8,000 rpm) to discard insoluble debris. 50,000 macrophages were isolated by cell sorter (S3e Cell Sorter, BioRad) as described in the section Isolation of macrophages. For analysis of fat body metabolites, the fat body from six flies was dissected and homogenized in ice‐cold PBS. Fraction of fat body was used for quantification of carbohydrates and part was used for isolation of lipid fraction by adapted Bligh and Dyer method for assaying of cholesterol, cholesteryl‐ester, and triglycerides. The concentration of metabolites was normalized per protein in the sample. Half of all samples were used for the quantification of proteins. Samples for glucose, glycogen, trehalose, and glyceride measurement were denatured at 75°C for 10 min, whereas samples for protein quantification were frozen immediately at −80°C. Glucose was measured using a Glucose (GO) Assay (GAGO‐20) Kit (Sigma) according to the manufacturer's protocol. The colorimetric reaction was measured at 540 nm. For glycogen quantification, a sample was mixed with amyloglucosidase (Sigma) and incubated at 37°C for 30 min. A Bicinchoninic Acid Assay (BCA) Kit (Sigma) was used for protein quantification according to the supplier's protocol and the absorbance was measured at 595 nm. Cholesterol and cholesteryl esters were measured on isolated lipid fractions by using Cholesterol/Cholesteryl Ester Quantitation Kit (Sigma) according to the supplier's protocol. Glycerides were measured using a Triglyceride quantification Colorimetric/Fluorometric Kit (Sigma). For trehalose quantification, a sample was mixed with trehalase (Sigma) and incubated at 37°C for 30 min. Samples for metabolite concentration were collected from three independent experiments.

Flies were dissected in Grace's Insect Medium (Sigma) and subsequently stained with DAPI and Cell Brite Fix Membrane Stain 488 (Biotium) diluted with Grace's Insect Medium according to the manufacturer's protocol at 37°C. Tissues were washed in PBS and then fixed with 4% PFA (Polysciences). After 20 min, the tissues were washed in PBS and pre‐washed with 60% isopropanol. Dissected abdomens were then stained with OilRedO dissolved in 60% isopropanol for 10 min. The tissues were then washed with 60% isopropanol and mounted in an Aqua Polymount (Polysciences). Tissues were imaged using an Olympus FluoView 3000 confocal microscope (Olympus). The content of lipids in adipose tissue and the size of lipid droplets were analyzed using Fiji software. Flies for the analysis of lipid droplets in the fat body were collected from three independent experiments and representative images are shown.

Fat bodies from six flies and one hundred thousand isolated macrophages were obtained for each analyzed group. Tissue lipid fraction was extracted by 500 μl of cold chloroform: methanol solution (v/v; 2:1). The samples were then homogenized by a Tissue Lyser II (Qiagen, Prague, Czech Republic) at 50 Hz, −18°C for 5 min and kept further in an ultrasonic bath (0°C, 5 min). Further, the mixture was centrifuged at 10,000 rpm at 4°C for 10 min followed by the removal of the supernatant. The extraction step was repeated under the same conditions. The lower layer of pooled supernatant was evaporated to dryness under a gentle stream of Argon. The dry total lipid extract was re‐dissolved in 50 μl of chloroform: methanol solution (v/v; 2:1) and directly measured using previously described methods (Bayley et al, 2020). Briefly, high‐performance liquid chromatography (Accela 600 pump, Accela AS autosampler) combined with mass spectrometry LTQ‐XL (all Thermo Fisher Scientific, San Jose, CA, USA) were used. The chromatographic conditions were as follows: Injection volume 5 μl; column.

Gemini 3 μM C18 HPLC column (150 × 2 mm ID, Phenomenex, Torrance, CA, USA) at 35°C; the mobile phase (A) 5 mM ammonium acetate in methanol with ammonia (0.025%), (B) water and (C) isopropanol: MeOH (8:2); gradient change of A:B:C as follows: 0 min: 92:8:0, 7 min: 97:3:0, 12 min: 100:0:0, 19 min: 93:0:7, 20–29 min: 90:0:10, 40–45 min: 40:0:60, 48 min: 100:0:0, and 50–65 min: 92:8:0 with flow rate 200 μl/min. The mass spectrometry condition: positive (3 kV) and negative (−2.5 kV) ion detection mode; capillary temperature 200°C. Eluted ions were detected with full scan mode from 200 to 1,000 Da with the collisionally induced MS2 fragmentation (NCE 35). Data were acquired and processed by means of XCalibur 4.0 software (Thermo Fisher). The corrected areas under individual analytical peaks were expressed in percentages assuming that the total area of all detected is 100%. Lipidomics data were subsequently analyzed in the online platform LipidSuite (https://suite.lipidr.org/; Mohamed & Hill, 2021). Data were inputted by the K‐Neares Neighbors method (KNN), and normalization was performed by the PQN algorithm. Subsequently, data were explored by PCA and OPLS‐DA methods. Differential analysis of lipidomic data was done by univariate analysis and visualized in Volcano plots.

Flies were dissected in ice‐cold PBS and fixed with 4% PFA in PBS (Polysciences) for 20 min. After three washes in PBS‐Tween (0.1%), nonspecific binding was blocked by 10% NGS in PBS for 1 h at RT. Tissues were then incubated with primary antibodies (for NimC1: Mouse anti‐NimC1 antibody P1a + b, 1:100, kindly provided by István Andó (Kurucz et al, 2007); for Foxo: Rabbit anti‐Foxo, CosmoBio, 1:1,000; for tGPH: Rabbit anti‐GFP, ABfinity, 1:100) at 4°C overnight. After washing the unbound primary antibody (three times for 10 min in PBS‐Tween), the secondary antibody was applied at a dilution of 1:250 for 2 h at RT (Goat anti‐Mouse IgG (H + L) Alexa 555, Invitrogen or Goat anti‐Rabbit IgG (H + L) Cy2, Jackson‐Immunoresearch). Nuclei were stained with DAPI. Tissues were mounted with Aqua Polymount (Polysciences). Tissues were imaged using an Olympus FluoView 3000 confocal microscope (Olympus) and images were reconstructed using Fiji software. Foxo localization was detected by Plot‐Profile analysis using Fiji software. For tGPH activity, confocal images were analyzed by using a plot profile (FIJI) under an arbitrarily defined line connecting two nuclei of neighboring cells and crossing the membrane in the middle. The ratio between cytosolic and membrane signals is displayed in the plot.

For assaying 13C‐FFA distribution post‐infection, males were fed standard fly food covered on its surface with 50 μl ¹³C Fatty Acid Mix (Cambridge Isotope Laboratories), 5 mg/ml in chloroform per each vial for 5 h. After 5 h FFAs can be detected in the gut, but are not incorporated into other body compartments (as documented by Bodipy‐labeled FFAs). Thereafter, the flies were split into control and experimental groups and injected with buffer or S. pneumoniae, and transferred to a fresh vial containing unlabeled food. After 24 h, six guts and six fat bodies were dissected in PBS and 50,000 macrophages were isolated by cell sorter from 160 individuals. Lipid fraction from the samples was isolated through the standard Bligh and Dyer procedure and free fatty acids were deliberated from complexes by a lipase from Aspergillus niger. Homogenized and filtered chloroform extracts (100 μl) were put in glass inserts in 2 ml chromatographic vials and their 13C enrichment was analyzed compound‐specific. 1 μl was injected in a split/splitless injector of a gas chromatograph, GC (Trace 1310, Thermo, Bremen, Germany), injector at 250°C. The injection was splitless for 1.5 min, then split with flow 100 ml/min for the next 1 min, and 5 ml/min (gas saver) for the rest of the analysis. Semipolar capillary column Zebron, ZB‐FFAP (Phenomenex, Torrance CA, USA, 30 m × 0.25 mm × 0.25 μm film thickness) with a flow rate of 1.5 ml/min of helium was used as a carrier. The temperature program was: 50°C during injection and for the next 2 min, then 50–200°C with a slope of 30°C/min, 200–235°C with a slope of 3°C/min, and hold at 235°C for the rest 32 min (total run time ca 51 min). Eluting compounds were oxidized to CO₂ via IsoLink II interphase (Thermo, Bremen, Germany) at 1000°C and introduced to continuous‐flow isotope ratio MS (Delta V Advantage, Thermo, Bremen, Germany). Compounds were identified using retention times of fatty acid standards. 13C sample abundance was expressed in At‐% 13C and “13C excess” calculated as follow:where A13Cs is the absolute 13C abundance of labeled samples and A13Cn absolute 13C abundance of natural lipids.

For transcriptomic analysis, macrophages from flies infected by S. pneumoniae or injected with PBS were isolated by cell sorter as described in the section “Isolation of macrophages”. Two hundred thousand macrophages were used for the isolation of RNA by TRIzol (Ambion). Sequenation libraries were prepared by using siTOOLs riboPOOL D. melanogaster RNA kit (EastPort) followed by subtraction of ribosomal fraction by NEBNext Ultra II Directional RNA kit (Illumina). The quality of prepared RNA libraries was assayed by Bioanalyzer and all samples reached an RIN score over the threshold of 7. Sequencing analysis was performed by using the NovaSeq instrument (Illumina). Raw sequencing data were processed by standard bioinformatics workflow for trimming barcodes and adapters. Trimmed reads were aligned to reference D. melanogaster genome BDGP6.95 (Ensembl release). Trimming, mapping, and analysis of quality were performed in CLC Genomic Workbench 21.0.5 software via standard workflow for RNA‐seq and Differential gene expression analysis. A subsequent search of transcriptomic data for enhanced and silenced pathways and biological processes was done by using TCC (Sun et al, 2013), and iDep94 (Ge et al, 2018) platforms combined with String and FlyMine databases.

The Pro‐A Drosophila CHIP Seq Kit (Chromatrap) was used to co‐immuno‐precipitate genomic regions specifically bound by the transcription factor HIF1α. A transgenic fly strain carrying the Hif1α protein fused to GFP (BDSC: 42672) was used for this purpose. The procedure was performed according to the supplier's instructions. Briefly, the slurry was prepared by homogenizing 10 infected or PBS‐injected males in three biological replicates. The Rabbit Anti‐GFP antibody (ABfinity) was bound to the chromatographic column. Genomic DNA was fragmented to an approximate size of 500 bp by three cycles of 60‐s sonication. The fragment size was verified by gel electrophoresis. All samples were tested with positive and negative controls. The amount of precipitated genomic fragments was normalized to the number of fragments in the slurry before precipitation. The ImpL2‐RA promoter sequence was covered with seven primer pairs corresponding to the 500‐bp bins upstream of the transcription start site previously assessed in the in silico analysis. The genomic region of S‐adenosylmethionine synthetase was used as a negative control since it does not contain any sequences of hypoxia response elements. Primer sequences are listed in the Key Resources Table. The amount of HIF1α‐bound regions of the ImpL2 promoter was quantified on a 96CFX 1000 Touch Real‐Time Cycler (BioRad) using TP 2× SYBR Master Mix (Top‐Bio) in three technical replicates with the following protocol: initial denaturation—3 min at 95°C, amplification—15 s at 94°C, 20 s at 56°C, 25 s at 72°C for 40 cycles. Melting curve analysis was performed at 65–85°C/step 0.5°C. The qPCR data were analyzed using double delta Ct analysis.

To analyze the phagocytic rate, flies were infected with 20,000 S. pneumoniae and after 24 h, they were injected with 50 nl of pHrodo™ Red S. aureus (Thermo Fischer Scientific). After 1 h, the abdomens of flies were dissected in PBS and then fixed for 20 min with 4% PFA. Aqua Polymount (Polysciences) was used to mount the sample. Macrophages were imaged using an Olympus FluoView 3000 confocal microscope and red dots depicting phagocytic events were manually counted per cell.

To analyze lipoprotein uptake by Drosophila macrophages, Buff injected or infected Crq > GFP flies were injected at 24 hpi with pHrodo™ Red LDL (Invitrogen) into the ventrolateral side of the abdomen using an Eppendorf Femtojet microinjector. After 1 h, the fly abdomens were opened in PBS and subsequently fixed for 20 min with 4% PFA in PBS (Polysciences). Aqua Polymount (Polysciences) was used to mount the sample. Macrophages were imaged using an Olympus FluoView 3000 confocal microscope. LDL pHrodo signal was counted manually from 10 flies for each group.

THP‐1 cells were cultured at 37°C, 5% CO₂, in RPMI‐1640 medium (Sigma), supplemented with 2 mM glutamine (Applichem), 2 g/l sodium bicarbonate (J&K Scientific), 10% FBS (Biosera) and 100 mg/l streptomycin (Sigma). Prior to the experiment, cells were transferred to 24‐well plates at 10⁵ cells/well in four biological replicates. THP‐1 cells were activated with phorbol‐12‐myristate‐13‐acetate (200 ng/ml, MedChemExpress). After 24 h, S. pneumoniae bacteria were added (MOI 50 bacteria/macrophage) or LPS (100 ng/ml; and the plate was centrifuged briefly (2 min, 200 g). Following 6‐h incubation, the cells were washed with RPMI‐1640 medium, and fresh RPMI‐1640 supplemented with gentamycin (0.1 mg/ml, Sigma) was added. After 1 h incubation, the medium was replaced with RPMI‐1640 supplemented with penicillin–streptomycin (1%, Biosera). After another 17 h, the cells were harvested into TRIzol Reagent (Invitrogen) followed by RNA isolation. In experiments with Hif1α agonist (DMOG—50 mg/ml) and antagonist (KC7F2—25 mg/ml), the Hif1a‐affecting drugs were administered 24 h before exposure of cells to LPS. DMSO was used instead of drug treatments in controls. For quantification of IGFBP7 concentration, the media were harvested and diluted 1:10. IGFBP7 protein level was quantified according to the manufacturer's protocol (Human IGFBP7/Igfbp Rp1 ELISA Kit PicoKine, BosterBio).

Glucan shells (GS) were prepared by using a previously published protocol (Tesz et al, 2011). Briefly, 100 g of baker's yeast (Saccharomyces cerevisiae, SAF‐Mannan, Biospringer) was heated at 80–85°C for 1 h in 1 l of NaOH (0.5 M) to hydrolyze the outer cell wall and intracellular components. This step was repeated after a water wash. Following centrifugation (15,000 g for 10 min), the resulting pellet was washed at least three times with water and three times with isopropanol. This yielded approximately 3–4 mg of purified, porous 2‐ to 4‐μm, hollow β 1,3‐d‐glucan particles. One gram of empty β1,3‐d‐glucan particles resuspended in 100 ml of sodium carbonate buffer was then labeled with FITC by incubation with 10 mg of 5‐(4,6‐dichlorotriazinyl) amino fluorescein (DTAF) dissolved in 10 ml of ethanol for ~16 h protected from light. Labeled GS were then washed at least five times in water. Wild‐type mice fed an HFD for 8 weeks were first randomized according to their body weight and glucose tolerance. Mice were then treated with 12.5 mg/kg GeRPs loaded with siRNA (247 μg/kg) and Endoporter (2.27 mg/kg). Mice received six doses of fluorescently labeled GeRPs by intravenous injection over 15 days. For details concerning this experiment view part Methods and Supplementary Methods in (Tencerova, 2020).

Cryopreserved primary human hepatocytes (Bioreclamation IVT) were cultured in 96‐well ultra‐low attachment plates (Corning) as previously described (Tencerova, 2020). Briefly, 1,500 cells/well were seeded in culture medium (Williams' medium E containing 11 mM glucose supplemented with 2 mM l‐glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, 10 μg/ml insulin, 5.5 μg/ml transferrin, 6.7 ng/ml sodium selenite, and 100 nM dexamethasone) with 10% FBS as described previously. Following aggregation, cells were transitioned into serum‐free Williams' medium E (PAN‐Biotech) containing 5.5 mM glucose and 1 nM insulin for 7 days. On the day of the treatment, after 2 h of starvation, cells were exposed to recombinant human IGFBP7 (200 ng/ml; K95R, R&D Systems, 1334‐B7‐025 or wild type, R&D Systems, custom made) or insulin (100 nM) as reported previously (Tencerova, 2020). Protein was collected for immunoprecipitation assays and western blot analysis. Spheroid viability was controlled by ATP quantification using the CellTiter‐Glo Luminescent Cell Viability Assay (Promega) with values normalized to the corresponding vehicle control on the same plate. No statistically significant differences in viability were observed between IGFBP7‐ and vehicle‐treated controls when using heteroscedastic two‐tailed t‐tests (n = 8 spheroids) and P < 0.05 as the significance threshold (Morgantini et al, 2019). For analysis of lipoprotein production, the media were harvested and the level of LDL and VLDL was measured according to the manufacturer's protocol (Human Very Low‐Density Lipoprotein [LDL] and Human Very Low‐Density Lipoprotein [VLDL] Elisa Kit, respectively; Abbexa).

Box plots, heat maps, and donut graphs were generated in GraphPad Prism9 software. 2way ANOVA was used for multiple comparison testing, followed by Tukey's or Šídák's multiple comparisons tests. Ordinary one‐way ANOVA followed by Dunnett's multiple comparisons test was used to compare the results with the corresponding control group. An unpaired t‐test was used for pair reciprocal comparison of datasets. Bar plots display mean and standard deviation. The statistical significance of the test is depicted in plots by using the following GP code (P < 0.05 = *; P < 0.001 = **; P < 0.0001 = ***). Normality and homogeneity of variations were tested by the Anderson‐Darling test, D'Agostino Pearson's test, and Shapiro–Wilk test. Data showing significant deviances from normal distribution was normalized by Log₂‐transformation. For survival analyses, the data sets were compared by Log‐rank and Grehan‐Breslow Wilcoxon test. For complex differential analysis of omics data, we processed the data through an online platform for transcriptomic data analysis TCC (Sun et al, 2013)—based on the following R‐packages (edgeR, DESeq, baySeq, and NBPSeq), iDep95 (Ge et al, 2018)—based on the following R‐packages (limma, DESeq2, GSEA, PAGE, GACE, RactomePA, Kallisto, Galaxy) followed by subsequent analysis of assigned biological processes in Kegg pathways (www.genome.jp/kegg/pathway) and Flymine databases (https://www.flymine.org/flymine). An online platform for lipidomic data analysis (LipidSuite (Mohamed & Hill, 2021) – based on the R‐package lipidr) was employed for differential comparison of obtained lipidomic datasets.

List of primers and other nucleotide sequences used in this work:

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