Mating regulates growth, metabolism, and digestive efficiency in the female Drosophila midgut

Significance

Adaptive changes in organ size and function occur in most animals, but the significance of these and how they are regulated is not well understood. This paper describes changes in gene expression, physiology, metabolism, and digestion that occur in Drosophila females after mating. Some of these changes are controlled by steroid hormone (ecdysone) signaling. We present a foundation for future studies of adaptive changes in the gut after mating, and how these help the animal meet the demands associated with reproduction. Further studies of steroid- and reproduction-dependent changes in gut physiology can shed light on the health risks associated with pregnancy, lactation, and puberty, and may also help us understand the health risks of steroids used clinically.

Abstract

Adaptive changes in organ size and function occur in most animals, but how these changes are regulated is not well understood. Previous research found that mating in Drosophila females promotes intestinal stem cell proliferation and increases the overall size of the endodermal portion of the intestine (the “midgut”). Other studies reported mating-dependent changes in feeding behavior, midgut gene expression, and whole-body lipid storage, suggesting altered metabolism. Here, we show that mating dramatically alters female midgut metabolism and digestive function. Mating increased relative levels of TCA cycle intermediates, fatty acids, and ceramides in the gut, increased total midgut lipids and protein, and reduced relative carbohydrate levels. Mating also enhanced the efficiency of protein digestion relative to carbohydrate digestion. Corroborating a previous report [M. A. White, A. Bonfini, M. F. Wolfner, N. Buchon, Proc. Natl. Acad. Sci. U.S.A. 118, e2018112118 (2021)], we found that the expression of genes that mediate protein and carbohydrate and metabolism was similarly altered. In addition, we noted a mating-dependent downregulation of oxidative stress response and autophagy genes. Mating-dependent increases in ecdysone receptor (EcR) signaling were important for increasing TCA cycle intermediates, protein, and ceramides in the female midgut, but had minimal effects on bulk lipid accumulation. Overall, this study contributes to our understanding of the physiological changes that occur during adaptive intestinal growth, and how they are regulated.

Adaptive changes in organ size and physiology are crucial for the survival and optimal health of adult animals. Such adaptive changes occur in response to internal and external changes, including alterations in an organism’s physiological state, nutritional state, and environment. In mammals, adaptive growth of the intestine during pregnancy and lactation can be more than double to size of the organ, and this is crucial to meet the increased nutritional requirements (1–5) of both the mother and her offspring. This requires a complex interplay of hormonal, growth factor, and nutritional signals that regulate structural and functional changes in the gastrointestinal tract. Although progress has been made in understanding these mechanisms, many aspects remain incompletely understood (6–8). Ongoing research aims to better understand the molecular mechanisms and regulatory pathways involved in adaptive remodeling of the intestine.

In females of Drosophila melanogaster, mating causes significant changes in behavior, including increased egg-laying, decreased sexual receptivity, increased food consumption, increased preference for high-protein foods (9, 10), decreased immunity, and shortened lifespan (11–16). The reproductive performance of female flies, especially egg production, is directly related to their nutritional status, with higher protein intake required for higher fecundity (17, 18). Mating triggers a ~60% enlargement of the female midgut through the actions of 20-hydroxy-ecdysone (20HE) (9, 19–21), Sex Peptide (SP) (9), and juvenile hormone (JH) (21), which stimulate the proliferation of intestinal stem cells (19–22). Like vertebrate estrogen and testosterone, ecdysone is essential for developmental transitions and sexual maturation in insects (23), and it also influences physiological processes including metabolism and longevity (15, 24, 25). Transcriptomic and metabolomic analyses of whole flies have revealed a postmating metabolic shift favoring protein utilization and lipid production, which was proposed to not only facilitate greater fecundity but to make females more susceptible to bacterial toxicity and to shorten their lifespan (14). Female flies require the hormone Sex Peptide (SP), found in male seminal fluid, to trigger midgut enlargement and modulate the expression of digestive enzymes and metabolic genes after mating (9). Maternal food increase in mated flies through the enlargement of the crop in the anterior midgut is adaptive and regulated by Myosuppressin neurons. These neurons are targets of ecdysone, and have been shown to promote food intake (13). All these findings inform the central questions of this project, namely: What is the nature of mating-induced metabolic changes in the female gut, and how does ecdysone signaling regulate them?

Results

Mating-Induced Midgut Growth Alters Midgut Cell- and Chemical Composition.

We first sought to reproduce previous reports that mating promotes adaptive midgut growth in females. In our experiments, mated female flies were cultured with males, whereas unmated flies (virgins) were isolated from males shortly after eclosion. We allowed mating to begin 4 d after eclosion, and to proceed for 2 d at 25 °C. After 2-d of mating (6 d posteclosion), we dissected the midguts and quantified the numbers of esg⁺ progenitor cells, and midgut areas by immunofluorescent staining. Consistent with previous reports (9, 19–21), mated females had larger intestinal areas in the R2 and R4 regions (Fig. 1 A and B) and ~73% more esg+ progenitor cells in the R4 region (ISC and EB; Fig. 1D), though no significant difference in esg+ cell numbers was detected in R2 region (Fig. 1C). We also assayed the total number of cells by fluorescence-activated cell sorting (FACS) of isolated nuclei, after 5 d of mating (9 d posteclosion). This timepoint was chosen as reasonable endpoint of adaptive gut growth, because it correlates well with the timing of maximal postmating egg production (19). This revealed a large (~75%), reproducible increase in total nucleus (and cell) numbers (Fig. 1H), consistent with a previous report (21). Distributions of nuclear ploidy values were not significantly changed, however, with nuclei from mated and unmated fly’s intestines showing similar distributions of nuclei ranging from 2C to 64C in DNA content (Fig. 1I). Since DNA ploidy values typically parallel cell sizes, this indicates that mating-dependent midgut growth is driven primarily by increases in cell numbers rather than by increased cell sizes. This is consistent with previous reports showing increased intestinal stem cell (ISC) divisions after mating, but minimal enlargement of mature enterocytes (19–21).

Fig. 1.

Mating induces region-specific adaptive midgut growth and alters overall midgut composition. (A–E) 48 h mating, (H and I) 5 d mating. (A) R2 region area measurement of mated and unmated flies (esg-Gal4^ts). (B) R4 region area measurement of mated and unmated flies (esg-Gal4^ts). (C and D) Progenitor cell counts in the R2 (C) and R4 (D) regions of mated and unmated flies (esg-Gal4^ts). (E) Total protein content/gut comparing mated and unmated flies defined by colorimetric assay in mated (three replicates/15 guts) and unmated flies (three replicates/15 guts) (Act-Gal4^ts). (F) Total lipid content (pmol) defined by LC–MS of mated flies (four replicates/40 guts) and unmated flies (four replicates/ 40 guts) (esg-Gal4^ts). (G) Total carbohydrate content/gut defined by colorimetric assay in mated (three replicates/15 guts) and unmated flies (three replicates/15 guts) (Act-Gal4^ts). (H) Histogram depicting FACS-sorted nuclei from mated and unmated fly midguts, using 25 midguts/sample (genotype: esg-Gal4^ts). (I) Ploidy distributions of FACS-sorted midgut nuclei from the samples in H.

We next sought to learn how mating affects the composition of macromolecules, including proteins, lipids, and carbohydrates in the gut. As determined by a colorimetric assay, total absolute midgut protein content showed significant (~60%) increases after mating (Fig. 1E), paralleling the increase in total cell numbers. Likewise, lipidomics analyses by mass spectrometry showed large (~100%) increases in total absolute midgut lipid amounts, per midgut, in mated flies (Fig. 1F). However, total midgut carbohydrate contents, quantified using a colorimetric assay, showed that mated flies had only small, statistically insignificant increases in carbohydrate contents (Fig. 1G). Comparisons of the relative changes in these midgut components after mating showed that the increase in lipid content (~100%) was greater than the increase in protein (~60%) or carbohydrate (~12%) content (Fig. 1 E–G). These changes in the relative amounts of macromolecules likely reflect alterations in midgut cell physiology and function.

Mating Alters Midgut TCA Cycle Metabolites.

Since mating changed overall midgut composition, we investigated how it alters the midgut metabolic profile. Steady-state metabolite profiling on isolated midguts by gas- or liquid chromatography-mass-spectrometry (GC-MS, LC–MS) showed significant mating-dependent increases in the gut’s content of specific lipids, carbohydrates, amino acids, and other small metabolites (Dataset S1). After sum-normalization to remove the effects of overall gut growth, analysis of GC-MS and LC–MS data revealed significant enrichments of metabolites of the tricarboxylic acid (TCA) cycle, amino acid metabolism, and intermediates in fatty acid and carbohydrate metabolism (Figs. 2A and 6C). Increased TCA cycle intermediates included fumaric acid (log2FC: 0.55, P-value < 0.05), malic acid (log2FC: 0.85, P-value < 0.05), and myo-inositol (log2FC: 0.64, P-value < 0.05; Fig. 6C and SI Appendix, Fig. S5A, and Dataset S1). TCA cycle metabolites have long been regarded as metabolic intermediates that are essential for both energy (NADH, ATP) production and the biosynthesis of macromolecules, including nucleotides, lipids, and amino acids. It is also increasingly recognized that TCA cycle metabolites also play important roles in regulating chromatin modifications, DNA methylation, and posttranslational modifications of proteins, thereby altering gene functions (26, 27).

Fig. 2.

Mating increases TCA cycle metabolites, TGs, ceramides, fatty acids, carbohydrates, and amino acids content in the gut. (A) GC-MS metabolite set enrichment overview in mated flies (Act-Gal4^ts) (four replicates/60 guts) compared to unmated controls (Act-Gal4^ts) (four replicates/ 60 guts). (B) LC–MS analysis-derived graphs show the enrichment of different classes of lipids in mated flies midgut (esg-Gal4^ts) (four replicates/ 40 guts), compared to unmated flies (esg-Gal4^ts) (four replicates/40 guts), the color of each bar shows the significance of the change; red shows a statistically significant change while gray shows insignificant change, the y-axis shows the log-2 fold changes, x-axis shows the lipid classes, green disc size shows the relative abundance of each class of lipid in the graph. (C) LC–MS analysis showing the top 25 altered lipid species (comparing mated and unmated flies’ midguts). All species had log-2-fold changes >1 and significant P-values (<0.05). Changes depicted in the heat map based on z-score. All data were normalized to sum during generation of the graphics in A–C.

Fig. 6.

EcR significantly affects metabolic processes related to protein metabolism. (A and B) GC-MS metabolite set enrichment analysis of changes in metabolites, comparing midguts from mated and unmated flies ± EcR-RNAi driven by Act-Gal4^ts (four replicates/condition, 60 midguts/replicate). We show changes in metabolic processes upon mating; the analysis revealed (A) changes in metabolic processes that were caused by mating and which were not affected EcR-RNAi expression, and also (B) changes in metabolic processes that occurred in mated flies and which were suppressed by EcR-RNAi. This latter class (B) included many metabolites involved in amino acid and protein synthesis, and some TCA cycle metabolites (Dataset S1). (C) GC-MS data analysis showing all detected metabolites comparing mated and unmated flies’ midguts ± EcR-RNAi driven by Act-Gal4^ts. The heat map uses sum-normalized data and depicts z-scores (four replicates/condition, 60 midguts/replicate).

Mating Increases Intestinal Triglycerides and Ceramides.

As noted above, mating increased both the total midgut lipid content and the fractional content of lipids relative to protein and carbohydrates (Fig. 1F). A detailed lipidomics analysis by LC–MS showed that mating-induced increases in lipids varied by class (Fig. 2B). Triglycerides and ceramides showed the greatest, most significant relative increases among all detected lipid species (Fig. 2C). Triglycerides are a principal form of stored fat that can be mobilized to generate energy via β-oxidation. Cytoplasmic lipid droplets, prevalent in ECs, are probably the main source of triglycerides in the midgut, and become more abundant after mating (21). Ceramides are known to sustain the proliferation of ISCs by promoting the utilization of fatty acids (28) and have been proposed to be instructive for cell growth in some instances (29, 30). GC-MS showed that fatty acids, especially linoleic acid (log2FC = 0.72, P < 0.05) and lauric acid (log2FC = 1.0, P < 0.05) were also increased their relative fractions in the midguts of mated flies, suggesting changes in fatty acid synthesis and/or utilization (SI Appendix, Figs. S5A and S6C and Dataset S1). Linoleic acid is a major component of phospholipids in cell membranes and is essential for successful egg production and viability (31). It can also be metabolized for energy, which is critical during times of high metabolic demand or rapid growth, such as during egg production. Similarly, lauric acid can be used either for the synthesis of more complex lipids, which were dramatically increased in the midgut after mating, or metabolized for energy. As the longest of the medium-chain fatty acids, lauric acid can be transported into mitochondria either directly or through the carnitine shuttle as a fast source for β-oxidation, Acetyl-CoA, and ATP. Consistently, the relative abundance of acylcarnitine 12:0, a product of lauric acid that is shuttled into mitochondria, more than doubled in the midguts of mated flies than in unmated flies (33.7 vs. 14.7 pMol; see Dataset S1). These results emphasize the major physiological changes induced by mating in females. The midguts of mated females were not only larger; they showed widespread, significant changes in the relative abundances of specific metabolites, including in TCA cycle intermediates, amino acids, fatty acids, triglycerides, and ceramides in sum-normalized data. This indicated major alterations in the regulation and function of metabolic pathways during mating-dependent midgut remodeling.

Mating Alters mRNA Expression in Midgut Progenitor and Differentiated Cells.

Previous studies reported major changes in intestinal gene expression in response to both sex determination (32) and mating (9, 21) in females. To learn more about how mating drives midgut growth and remodels midgut physiology and metabolism, we performed mRNA sequencing (RNAseq) on both FACS-sorted esg+ progenitor cells and whole guts from mated and unmated females (Dataset S2) (33). RNAseq profiles taken at 48 h after the initiation of the 2 d window of mating showed significant changes in the relative levels of mRNAs for genes involved in many metabolic processes, including but not limited to: upregulation of Jonah-type serine endopeptidases used in protein digestion (Jon99Fii, Jon99Cii, Jon44E, Jon65Ai, Jon25Bi, Jon25Bii, Jon99Ciii, Jon65Aiv, Jon65Aiii) (SI Appendix, Fig. S1A); upregulation of genes encoding amino acid transporters (dmGlut, slif, NAAT1); and relative downregulation of maltases and other genes involved in carbohydrate catabolism (Mal-A4, Mal-A7, Mal-A8, Mal-6, Mal-1, Mal-2). RNAseq analyses of FACS-isolated esg+ progenitor cells showed similarities to these trends in the whole midgut and also revealed a progenitor cell-specific mating-dependent downregulation of Gst family genes (GstD2, GstD5, GstD6, GstD9, GstE1, GstE3, GstE6, GstE7, GstE8, GstE9, GstO3, GstT4), which are involved in combating oxidative stress (Fig. 3E, SI Appendix, Fig. S1A, and Dataset S2). Gene Ontology (GO) enrichment analysis of the whole midgut RNAseq data confirmed that mating generally upregulates genes involved in proteolysis and downregulates genes involved in carbohydrate metabolic processes (Fig. 3 A–D). Gene set enrichment analysis (GSEA) further confirmed these trends (SI Appendix, Fig. S1 B and C). GO enrichment analysis of whole midgut RNAseq also revealed mating-dependent downregulation of the majority of autophagy-related genes, including Atg1, Atg2, Atg3, Atg4b, Atg9, Atg18a/b, Atg101, and Rab18 (GO:0000045 and GO:0005776) (Fig. 3F). Interestingly, this trend was not observed in esg+ progenitor cells, which showed a reverse trend (SI Appendix, Fig. S4A and Datasets S2 and S3). Finally, we noted another set of genes with significant differential expression in FACS-sorted esg+ cells, namely genes involved in stress responses (SI Appendix, Fig. S1D), including heat shock proteins (Hsp) and oxidative stress response genes (SI Appendix, Fig. S1 A, D, and E). Most of these genes were downregulated in the midgut by mating. Notably, a previous study (9) identified similar classes of midgut genes altered by mating and dependent on male-derived Sex Peptide, our study reveals significant transcriptional downregulation of autophagy-related genes and Gst family genes in progenitor cells after mating.

Fig. 3.

Mating upregulates protein metabolism gene expression and downregulates carbohydrate metabolism and oxidative stress response, and autophagy gene expression. (A) GO enrichment analysis showing upregulated pathways in guts of mated flies (esg-Gal4^ts) compared to unmated ones (esg-Gal4^ts) (each/four replicates/15 guts) (Whole midgut RNAseq). (B) GO enrichment analysis showing downregulated pathways in guts of mated flies (esg-Gal4^ts) compared to unmated controls (esg-Gal4^ts) (each/four replicates/15 guts) (Whole midgut RNAseq). (C–F) Targeted heat maps for the significantly differentially expressed genes classified under the GO terms “protein metabolic process” (whole midgut RNAseq; C), “carbohydrate metabolic process” (whole midgut RNAseq; D), “oxidative stress response metabolic process” (FACS-sorted esg+ cells RNAseq; E) and “autophagy-related GO terms” (whole midgut RNAseq; F).

To gain more insight into the regulation of the metabolic pathways changed by mating, we considered our metabolite and RNAseq profiling datasets together. Lipidomics analysis clearly showed increases in midgut triglycerides (TG), a storage form of lipid, and RNAseq showed significant upregulation of genes including the triacylglycerol lipase brummer (bmm) (SI Appendix, Fig. S1A), which is used to mobilize stored (and perhaps dietary) fats (34). GC-MS showed increases in fatty acids, which are the precursors for TG production. Our GC-MS metabolomics data also showed significant changes in amino acids, including arginine, tryptophan, and valine, which all increased after mating. Confirming the previous findings of White et al. (9) our gene expression datasets showed the upregulation of the Jonah genes, which encode gut-specific serine-type endopeptidases that play a central role in the digestion of dietary proteins by breaking them down into smaller peptides and eventually amino acids for absorption. These Jonah genes are homologous to mammalian serine proteases such as trypsin and chymotrypsin. Together, these results suggest that mating in female Drosophila leads to metabolic alterations in the midgut that favor the utilization of proteins and fats over the processing of carbohydrates, probably to meet the increased energy and biosynthetic demands associated with egg production.

Mating-Dependent Changes in Bulk Midgut Lipids and Carbohydrates Are Ecdysone Signaling-Independent.

Next, we sought to understand whether these mating-induced changes in metabolite and transcriptome profiles were due to ecdysone signaling, which we and others previously identified as instructive for promoting mating-dependent midgut growth and female fecundity (19, 20). To investigate how the ecdysone signaling pathway affects mating-induced changes, we compared mated and unmated flies, each expressing or not expressing RNAi directed against the Ecdysone Receptor, EcR. While previous studies (19, 20) had focused on EcR-dependent functions in intestinal progenitor cells (ISC, EB) using the progenitor cell-specific driver esg-Gal4^ts, we employed conditional (temperature-sensitive) versions of the ubiquitously expressed Actin-Gal4 (Act-Gal4^ts) and enterocyte (EC)-specific Myosin1A-Gal4 (Myo1A^ts) drivers to assess potential EcR-dependent functions in other cell types. We aged unmated flies for 5 d at 29 °C to express EcR-RNAi, and then we mated the flies for 48 h (at 25 °C). Finally, we dissected the guts after 48 h of mating for sample preparation.

As shown above (Fig. 1F), mating increased the total lipid content of the Drosophila female intestine, with phospholipids, triglycerides, and fatty acids accounting for the bulk of the increase (Fig. 2B), and ceramides and triglycerides showing the most significant increases (Fig. 2C). In similar LC–MS lipidomics tests performed after treatment with EcR-RNAi, we found that the total increase in lipid content in response to mating was not significantly changed (Fig. 4A) and that fat metabolism genes such as bmm were not affected by EcR-RNAi (Dataset S4) (33). Likewise, EcR-RNAi had no detectable effect on midgut carbohydrate content (SI Appendix, Fig. S5B), which was in any case not significantly affected by mating (Fig. 1G). Consistently, mating-induced transcriptional downregulation of carbohydrate metabolism genes was not significantly affected by EcR-RNAi expressed in either the whole body (with Act-Gal4^ts) or the midgut (with Myo-Gal4^ts; SI Appendix, Fig. S4 B and C).

Fig. 4.

Mating-induced increase in ceramides is EcR-dependent. (A) Total absolute lipid contents derived from LC–MS comparing mated and unmated flies ± EcR-RNAi using Act-Gal4^ts, each/four replicates/40 guts. (B) LC–MS derived bar graphs show enrichment of different classes of lipids in mated flies compared to unmated flies; green disk size shows the abundance of the corresponding lipid class in the graph. (C) LC–MS derived bar graphs show enrichment of different classes of lipids in mated flies with EcR-RNAi expression (Act-Gal4^ts) compared to genotype-matched unmated flies; green disk size shows the abundance of the corresponding lipid class in the graph. (D) Targeted heatmap from LC–MS data analysis showing relative changes in all detected ceramides, comparing mated and unmated flies’ midguts ± EcR-RNAi driven by Act-Gal4^ts. The heat map depicts z-scores derived from sum-normalized data, using four replicates/condition, 40 midguts/replicate.

Mating-Induced Increases in Midgut Ceramides Are Ecdysone Signaling-Dependent.

In contrast to bulk lipids (Fig. 4A) and the major lipid classes (Fig. 4 B and C), we found that the mating-dependent enrichment of most ceramide variants was significantly ablated by EcR-RNAi expressed under control of the ubiquitously active Act-Gal4 driver (Fig. 4 C and D and Dataset S1). Mating-induced ISC proliferation depends on both ceramide production (28) and on ecdysone signaling (19, 20), suggesting that EcR-RNAi could in theory suppress ISC proliferation by interfering with ceramide metabolism. However, the expression of genes in the proximal synthesis of ceramides (Schlank, Lace, Ifc, SMase, CDase, Bwa, Sk1, Sk2) was not significantly affected by either mating or by EcR-RNAi driven by Act-Gal4 (Datasets S2 and S4) (33), leaving the mechanism of ceramide upregulation in question.

Mating-Induced Increases in Midgut Protein Content Are Ecdysone Signaling-Dependent.

Whereas mating increased the total protein content of female fly midgut (Fig. 1E), the guts of mated flies expressing EcR-RNAi largely failed to grow and did not show a significant increase in protein (Fig. 5 A–C). This dramatic suppression of midgut protein accumulation was observed when EcR-RNAi was expressed under the control of either the ubiquitously expressed Actin-Gal4^ts driver (Fig. 5A), or the Myo1A-Gal4^ts (Fig. 5B), which is expressed specifically in enterocytes (ECs) in the midgut but also some neurons. To ensure enterocyte-specificity and avoid confounding neuronal expression, we used the Mex-Gal4^ts driver, which is restricted to differentiated enterocytes and does not express in gut-innervating neurons (13). This confirmed that the increase in total midgut protein after mating is EcR-dependent, and largely dependent on EcR function specifically in enterocytes. To further test the gut-specific role of ecdysone signaling, we induced RNAi directed against the Ecdysone Importer (EcI) using Mex-Gal4^ts. This produced a similar phenotype to Mex-Gal4^ts>EcR RNAi (Fig. 5D). These results align nicely with previous reports that used the esg-Gal4^ts and Su(H)-Gal4^ts drivers (9, 19) which are expressed in ISCs and/or EBs, to show that mating-dependent midgut growth is EcR-dependent. Our results provide the additional insight that EcR signaling specifically in ECs plays a role in mating-dependent midgut growth.

Fig. 5.

Mating-dependent upregulation of genes involved in protein metabolism requires EcR. (A–C) Total protein content defined by BCA colorimetric assay comparing mated and unmated flies (each/three replicates/5 to 15 guts) ± EcR -RNAi using Act-Gal4^ts (A), Myo1A-Gal4^ts (B), and Mex-Gal4ts drivers (C). (D) Total protein content comparing mated and unmated flies (each/three replicates/five guts) ± EcI -RNAi using Mex-Gal4^tsdriver. (E and F) GSEA comparing protein metabolic process genes expression in mated vs. unmated flies with (F) or without (E) EcR-RNAi expressed from the Actin-Gal4^ts driver. Enrichment Score (ES) measures how much a gene set is overrepresented at either end of a ranking list; Normalized Enrichment Score (NES) reflects the degree of this enrichment, shown on the y-axis. GSEA normalizes the ES to account for differences in gene set sizes and their correlations with expression data.

Mating-Dependent Upregulation of Protein Metabolism Genes Is Ecdysone Signaling-Dependent.

To learn more about how mating-dependent increases in midgut protein are regulated we performed additional RNAseq analysis. We aged the unmated flies for 5 d at 29 °C to express EcR-RNAi under the control of the Act-Gal4 driver. We then mated the flies for 48 h at 25 °C, and finally dissected guts 48 h after the initiation of mating for RNAseq analysis. Mated females expressing EcR-RNAi under the control of the Actin-Gal4^ts driver showed altered transcriptomes compared to controls not expressing RNAi. Gene Ontology (GO) enrichment analysis revealed that GO terms related to protein metabolism were the most affected. Consistent with results shown earlier, GO terms such as proteolysis (GO: 0006508), amino acid transport (GO: 0006865), carboxylic acid transmembrane transport (GO: 1905039), and amino acid transmembrane transport (GO: 0003333) were significantly upregulated by mating in the midgut (SI Appendix, Fig. S3A). However, the statistical significance of the upregulation of protein metabolism genes was very strongly reduced in mated flies expressing EcR-RNAi (SI Appendix, Fig. S3A), suggesting that ecdysone signaling is critical for the regulation of these genes and processes after mating. Gene Set Enrichment Analysis (GSEA) confirmed that EcR signaling controls mating-induced changes in the expression of a broad range of protein metabolism genes, including genes involved in proteolysis and amino acid transport (Fig. 5 E and F). However, this EcR-specific effect was not observed when EcR-RNAi was expressed with the EC-specific Myo1A-Gal4^ts driver (SI Appendix, Fig. S3 C and D), suggesting that EcR-mediated regulation of protein metabolism genes occurs in a non-EC cell type, possibly outside the midgut. This is consistent with recent studies indicating an important role for foregut cells in protein metabolism (35). The markedly stronger effects observed with Act>EcR RNAi compared to Myo1A>EcR RNAi may also reflect the broader systemic impacts of the former, including potential changes in feeding behavior and/or egg production.

Mating-Dependent Upregulation of Jonah Proteases Requires EcR.

Protein digestion requires both endo- and exo-peptidase enzymes. In Drosophila, Jonah family endopeptidases, yip7 and trypsin first split large ingested proteins at internal peptide bonds. The smaller peptides that result are then hydrolyzed to single amino acids, starting at their terminal ends, by exopeptidases such as carboxypeptidases (CG12374, CG17633), or to smaller peptides by di-peptidyl peptidases (CG3744, CG11034, CG17684, Dpp10, ome) (36). Subsequently, intestinal protein absorption requires amino acid transporters (Slif, NAAT, path) (9, 37) and oligopeptide transporters (Yin, CG2930, CG9444) (37) that transfer the digested protein into cells, most likely enterocytes. Our RNA-seq data showed that mating significantly increased the expression of many Jonah gene transcripts (Jon25Bii, Jon65Aii, Jon99Cii, Jon99Ciii, Jon65Aiii, Jon65Aiv, Jon25Bi, Jon44E, Jon66Ci, and Jon66Cii; SI Appendix, Fig. S1A) that encode serine endo-peptidases. Mating also increased the expression of other peptidases (trypsins, yip7, CG12374), as well as the amino acid importers Slif, NAAT, dmGlut, and path. As with the broader set of protein metabolism genes, EcR-RNAi under the control of Act-Gal4^ts significantly suppressed the mating-dependent upregulation of most of these genes (Fig. 5 E and F, SI Appendix, Fig. S3, and Dataset S4), but this inhibitory effect did not occur when EcR-RNAi was expressed specifically in enterocytes using the Myo1A-Gal4^ts driver (SI Appendix, Fig. S3). In addition, we noted that the expression of certain protein absorption genes (Yin, CG2930, CG9444, Slif, path) was not affected by EcR-RNAi under the control of either driver (Dataset S4). These results suggest that EcR regulates some, but not all, of the digestive steps of protein metabolism in mated females, and that this occurs through a non-EC autonomous function.

Ecdysone Signaling Modulates TCA Cycle, Lipid, and Protein Metabolism.

Based on the observations above we predicted that ecdysone/EcR signaling might preferentially regulate protein digestion and metabolism in mated females. To test this we performed metabolite profiling on the midguts of mated and unmated flies, each with or without EcR-RNAi conditionally expressed under the control of the Actin-Gal4 (Act-Gal4^ts) driver. We aged newly eclosed unmated flies for 5 d and shifted them to 29 °C to express EcR-RNAi. Half the flies were then mated for 48 h at 25 °C, whereas the rest (unmated samples) were cultured for 48 h at 25 °C without males. Midguts were then dissected for metabolite analyses. As noted above, TCA cycle intermediates were strongly upregulated by mating (Fig. 2A and SI Appendix, Fig. S5A). However, in the midguts of mated flies expressing EcR-RNAi, most of these TCA cycle intermediates were not significantly altered (Fig. 6 B and C and SI Appendix, Fig. S5A), indicating that mating-induced changes in these metabolites were EcR-dependent.

In contrast, our analyses showed that most changes in lipid metabolism were not affected by EcR-RNAi, regardless of mating status (Figs. 4 A–C and 6 A–C). Considering this and the effect of EcR-RNAi on ceramides and fatty acid enrichments in mated flies, we conclude that EcR is partially involved in lipid metabolism in mated flies. However, changes in metabolites associated with protein metabolism, such as changes in amino acids, were largely EcR-dependent in mated flies (Fig. 6 A–C and Dataset S1). Interestingly, the effects of mating and EcR-RNAi on free amino acids in the midgut paralleled the effects on expression of Jonah protease genes and other protein metabolism genes (Fig. 5 E and F and SI Appendix, Fig. S3 A and B) in as much as both amino acids and these genes are upregulated after mating and required EcR for this upregulation. In conclusion, loss of EcR altered the metabolic profile of mated flies by interfering with metabolic pathways responsible for the provision of TCA intermediates, amino acids, and ceramides. These metabolic effects are likely important for the ecdysone signaling-mediated activation of mating-dependent ISC proliferation and growth in the midgut (Figs. 1, 5 A–D, and 6) (19–21).

Mating Promotes Protein Digestion Efficiency.

Several studies have emphasized the importance of dietary protein (38) and protein metabolism (39, 40) for egg production by Drosophila females. Based on our observations we postulated that not only the preference for proteinaceous food (9–12, 41), but also the digestion and/or absorption of protein might be enhanced by mating. To test this idea we performed metabolomics analysis on feces collected from mated and unmated female flies (Dataset S1). This revealed higher relative levels of free amino acids in the feces of mated as compared to unmated flies (Fig. 7 A and B), consistent with the possibility that mated flies may have enhanced protein digestion (i.e. increased extracellular, luminal proteolysis), and with our RNAseq data showing mating-dependent upregulation of genes that encode secreted proteases, including the Jonah family endo-peptidases and trypsins (Fig. 3 A and C and SI Appendix, Fig. S1 A and B) (9). Further, the increase in fecal amino acids suggested that increases in protein digestion may out-pace increases in amino acid and small peptide absorption by the intestine. To learn more about this effect we assessed the protein and carbohydrate contents of the feces (Materials and Methods). Standard, homogenized fly media were used in all experiments, eliminating the possibility for animal food choice. Although the total amounts of fecal protein and carbohydrate showed merely that mated females eat much more than unmated females, the ratios of protein:carbohydrate in the fecal samples were informative. These ratios consistently showed relative reductions in fecal protein after mating, and relative increases in fecal carbohydrate (Fig. 7 C–F). Consistent with our hypothesis, this also suggests more efficient protein digestion in mated females than in unmated females. However, depleting the ecdysone receptor by expressing EcR-RNAi either in the whole fly body (using Act-Gal4^ts) or in enterocytes (using Myo1A-Gal4^tsor Mex-Gal4^ts) did not significantly alter the mating-dependent reductions in fecal protein/carbohydrate ratios (Fig. 7 C–E). A similar lack of effect was obtained after depleting the ecdysone importer, EcI, in enterocytes (Fig. 7F). This was somewhat perplexing because our RNA-seq data showed that mating-induced expression of protein digestion genes (e.g., Jonah-type endopeptidases) was significantly reduced by EcR-RNAi expressed under the control of Act-Gal4^ts (Fig. 3C and SI Appendix, Fig. S3B). This discrepancy might be attributed to the fact that the induction of absorption-related genes (e.g., amino acid and peptide transporters) was not appreciably reduced by EcR-RNAi (SI Appendix, Fig. S3A and Dataset S4).

Fig. 7.

Mating enhances protein digestion efficiency. (A) GC-MS analysis of feces shows the enrichment of metabolites (comparing mated and unmated flies’ feces, each/three replicates/70 flies) with log-2-fold changes >1 and P-values < 0.05, depicted in the heat map based on z-score. (B) GC-MS analysis-derived bar graphs show the enrichment of different classes of metabolites in mated flies feces (w1118) (three replicates/70 flies), compared to unmated (w118) (three replicates/70 flies), the color of each bar shows the significant of the change, red shows statistical significant change while gray color shows insignificant change, the y-axis shows the log-2 fold changes, and x-axis shows the values, green disc size shows the abundance of its correspondent class of lipid in the graph. (C–E) Protein/Carbohydrate ratios in mated and unmated flies ± EcR-RNAi using Act-Gal4^ts (C), Myo1A-Gal4^ts(D), and Mex-Gal4^ts (E). (F) Protein/Carbohydrate ratios in mated and unmated flies ± EcI-RNAi (Mex-Gal4^ts).

Discussion

We report here that mating induces significant physiological and metabolic changes in the female Drosophila gut. Confirming previous studies (19–21), we observed adaptive, mating-dependent growth of the midgut mediated by ecdysone signaling. This expansion is characterized by a larger midgut size and more total cells, including more progenitor cells. Mating-induced midgut growth was accompanied by changes in the gut’s biochemical composition: we observed large increases in total midgut lipids and protein in mated flies, while carbohydrate amounts were essentially unchanged. Our metabolomics analyses revealed that the amounts of several TCA cycle intermediates increased significantly in mated female guts, including fumaric and malic acids. These increases were evident even after sum-normalization to all detected metabolites, suggesting higher per-cell concentrations. TCA cycle products including NADH and FADH₂ power the mitochondrial electron transport chain and ATP synthesis (42), and so these changes likely reflect increased ATP utilization. Fumarate also acts as an electrophile during the succination of proteins, binding reactive thiol groups in cysteines and inactivating them. Fumarate can also reshape the epigenetic landscape by inhibiting histone and DNA demethylases (26, 42). Through these avenues increased fumarate may have widespread effects on gene expression. Another metabolite that showed significant relative increases in the midgut after mating is myoinositol, a precursor of the essential membrane phospholipid, phosphatidylinositol (PI), which functions in signal transduction, endoplasmic reticulum stress (unfolded protein response), energy metabolism, nucleic acid synthesis, and osmoregulation (43). Such examples from our metabolite profiling experiments highlight that mating alters myriad details of a wide spectrum of metabolic pathways, all presumably to maximize biosynthesis and energy production for the generation of large quantities of eggs by the mated female.

Our LC–MS analysis showed a striking increase in both the total and fractional lipid content in the guts of mated females. This may reflect a greater demand for stored energy in the form of triglycerides and fatty acids. Ceramides were also among the top classes of lipids with significant enrichment after mating. Ceramides participate in membrane structure and function, but are also in signal transduction, and high ceramide levels are associated with proliferation of progenitor cells in the intestines of flies, mice, and humans (28, 44). Whether ceramide enrichment is regulatory and instructive for other growth-associated metabolic changes in the gut is presently unclear, but is an intriguing possibility. Metabolomics also confirmed enrichments in fatty acids, which are precursors for most of the complex lipids used in cell growth. Fatty acids can also be an important alternative energy source to fuel the TCA cycle and ATP production. Furthermore, the lipid changes induced by mating, particularly increased ceramides, appeared to be partially dependent on ecdysone signaling. A previous study indicated that mating changes lipid metabolism through the activation of Sterol Regulatory Element Binding Protein (SREBP) (21). The overall increase in total midgut lipid content after mating is believed to support enhanced energy storage and utilization during reproduction, as previously discussed (15, 21).

Consistent with prior studies (9, 45, 46), our gene expression profiling tests detected the postmating up-regulation of Jonah endopeptidase and amino acid transporter genes. We also noted the mating-dependent upregulation of other genes used in protein digestion, such as trypsins, exo-peptidases, and the amino acid and small peptide transporters used by the intestine to absorb proteolyzed proteins. Conversely, genes used in carbohydrate metabolism and digestion were relatively downregulated. This is consistent with our observation that mating caused a relative reduction in midgut carbohydrate content, and a large increase in the fecal carbohydrate content. While we interpret the upregulation of Jonah peptidases as an adaptation for enhanced protein digestion postmating, previous studies have also implicated these enzymes in immune functions (47, 48). Our findings show additionally that many aspects of the mating-induced switch toward protein digestion are EcR-dependent (Figs. 5E and 6 and SI Appendix, Figs. S1 and S3). This underscores the idea that ecdysone-dependent protein metabolism in females is prioritized after mating to meet the increased biosynthetic demands of reproduction. Hudry et al. (32, 49) showed that genes used in cell division-related processes are more abundantly expressed in mated females, whereas genes used in carbohydrate metabolism and redox processes are preferentially expressed in males. This and other observations suggest physiological similarities between unmated females and males, implying that the mating-induced switch toward protein metabolism, promoted by ecdysone (50), could be a female-specific phenomenon. The mating-dependent upregulation of protein metabolism genes is unlikely to be merely a consequence of increased food intake, since we also observed simultaneous downregulation of carbohydrate metabolism, oxidative stress, autophagy, and other types of genes. Instead, we propose that the female midgut changes its digestive parameters after mating to adapt to the new nutritional requirements mandated by egg production. In support of this, we documented large decreases in fecal protein:carbohydrate ratios after mating, as well as increases in fecal free amino acids (Fig. 7), without changing the diet. A previous study by White et al. (9) also suggested this possibility, whereas others focused mostly on the mated female’s preference for a protein-rich diet (10–14, 38, 39).

Surprisingly, the apparent increase in protein digestion efficiency did not seem to require the Ecdysone Receptor (Fig. 7 C–F), despite our observation that ecdysone signaling was necessary for full induction of many of the genes that encode digestive peptidases (Fig. 5E and SI Appendix, Fig. S3B). Although further experiments are required to resolve this discrepancy, our data as they stand are consistent with the possibility that EcR signaling enhances some aspects protein digestion (e.g., peptidase expression), while others (e.g., peptide and amino acid uptake gene expression) are EcR-independent and more rate-limiting (SI Appendix, Fig. S3A). Alternately, it is possible the mating-dependent changes in fecal protein:carbohydrate ratios we observed were driven primarily by alterations in carbohydrate digestion, which were not EcR-dependent (SI Appendix, Fig. S4). Finally, the overall switch to enhanced protein digestive efficiency might be regulated by another, nonecdysone mating-dependent signal, such as Sex Peptide (9, 45, 51), Juvenile Hormone (21), or Neuropeptide F (10).

Related to this, Cognigni et al. (52) reported that reproduction affects the acid–base balance in the gut, such that mated, egg-producing females show acidification of excreta (feces) (52). They proposed that the fly midgut “can modulate the final composition of intestinal contents” (i.e., the feces) and that the metabolic demands of egg production are an important modulatory input. Our results are clearly consistent with this proposal, as we found that fecal protein:carbohydrate ratios were decreased after mating (Fig. 7 C–F). Older work on mammals, summarized by Charney and Dagher (53), references similar changes in fecal acid/base balance and also suggested the gut’s ability to adaptively modulate its digestive functions. Our results align nicely with these studies (52, 53) and add more direct evidence for the ability of the midgut to adapt to external stimuli (e.g., mating) by altering its digestive functions through changes in gene expression and metabolism. While food intake increases after mating, the transit rate of food through the intestine slows (52) due to the action of Sex Peptide, a hormone found in male semen (51, 52). This mating-dependent effect may be yet another means to increase nutrient absorption in a nutritionally demanding situation (52).

Our transcriptomic profiling also revealed a significant, widespread mating-dependent downregulation of genes involved in stress responses, especially oxidative stress-associated genes. This effect was far stronger in esg⁺ intestinal stem cells (ISC) and enteroblasts than in whole midgut mRNA. It suggests that ISCs in mated flies may have a unique ability to cope with Reactive Oxygen Species (ROS), which are produced by mitochondria and the gut microbiota and are expected to rise in concert with increases in the mated females’ nutritional throughput, energy production, and stem cell proliferative activity. We suggest that this decrease in oxidative stress gene expression may be due to the increased protein metabolism in mated females, which increases levels of methionine (Figs. 6C and 7A), a precursor of glutathione, an important ROS neutralizer (54). Increased glutathione might enable mated flies to cope with oxidative stress using the basal-level expression of glutathione-S-transferase (GST) genes.

Our experiments also revealed a widespread downregulation of autophagy-related genes upon mating that was EcR-independent (SI Appendix, Fig. S4D). Autophagic activity is typically low under growth-promoting conditions, such as during gut growth and egg production in our study, and is conversely elevated under growth-limiting conditions, such as during nutrient deprivation (55). Our finding that autophagy genes were downregulated in the midgut upon mating is consistent with a report that mutants in the autophagy gene Atg101 have a thicker midgut epithelium with enlarged enterocytes (56) and suggests that the suppression of autophagy may aid enterocyte growth and/or digestive functions after mating. Interestingly, autophagy gene expression was not generally downregulated in esg+ progenitor cells after mating, where in fact many autophagy genes were induced (SI Appendix, Fig. S4A). This suggests distinct roles and modes of regulation of autophagy in ISCs and enterocytes, and is consistent with reports that mTOR activity, a suppressor of autophagy, rises during ISC to enterocyte differentiation (57, 58). Genetic tests of the requirement for autophagy in ISCs have given contradictory results, with one report showing ISC loss after ATG gene suppression (59) and another documenting increased ISC proliferation (60).

Beyond fruit flies, adaptive growth of the intestine is well documented in pregnant and lactating female mammals (5, 61–64). The onset of this growth coincides with large increases in estrogen, progesterone, and corticosteroids during gestation. Steroid hormone levels drop postpartum, but intestinal growth continues during lactation when levels of the prolactin hormone remain high. Like estrogen, progesterone, and cortisol (65, 66), ecdysone is a cholesterol-derived female-biased steroid that controls aspects of sexual behavior, dimorphism, physiology, and reproductive function in insects (67). The similarity in the structures of these hormones, their sites of synthesis, regulated secretion, and actions on the reproductive system suggest that they may have similar actions in other organs too. If increased steroid titers in pregnant mammals are causal for intestinal growth (this has not yet been rigorously tested), their functions in mammals could be analogous to the effects of ecdysone in mated Drosophila females (19, 20).

In summary, mating in female Drosophila triggers extensive physiological and metabolic adaptations in the midgut that alter protein and lipid metabolism. We presume these changes optimize nutrient intake and utilization to support reproduction (SI Appendix, Fig. S6). We acknowledge that whole-body EcR downregulation may influence midgut remodeling indirectly through systemic effects, including reduced feeding (68), suppressed oogenesis (69), and altered juvenile hormone signaling (69); all of which are known to impact intestinal physiology (8, 13, 70). While our enterocyte-specific manipulations highlight a local role for EcR, our tests also suggested that nongut tissues contribute to the overall phenotypes we describe, and merit further investigation. Further studies of steroid- and reproduction-dependent changes in gut physiology can shed light on the health risks and needs associated with pregnancy, lactation, and perhaps puberty. Tracking sex hormone-mediated changes in gut metabolism in mammals might also help to evaluate the physiological effects and health risks of steroids used clinically, for instance, in hormone replacement and cancer therapies and sports doping. Future studies in this area could also reveal new ways to diagnose sex hormone-mediated metabolic disorders.

Materials and Methods

Drosophila Stocks and Husbandry.

D. melanogaster flies were grown on standard media (SI Appendix, Materials and Methods) and housed in incubators under controlled temperature and humidity conditions in a 12-h light–dark cycle. Culture vials containing the flies were replaced with fresh vials every 2 d. Control groups were generated by crossing w¹¹¹⁸ (VDRC #60000) flies with the corresponding Gal4 driver line. For transgene expression using the Gal4/Gal80^ts system, experimental crosses were maintained at 18 °C (permissive temperature for GAL80^ts) on standard medium. Animals of the desired sex and genotype were collected on Day 0 after eclosion and aged for 5 d at 29 °C (restrictive temperature for GAL80^ts) to induce UAS transgene expression. Adult guts were dissected after 48 h mating, as explained below, in the “mating experiment.”

Mating Experiments.

At least 10 to 15 unmated females of each genotype, for each condition and replicate, were collected at 18 °C upon eclosion. They were then aged at 25 °C for 4 to 5 d or at 29 °C (in experiments using EcR-RNAi) for approximately 5 d until mating began. The functionality of EcR RNAi line (BL29374; EcR RNAi 3) has been validated in previous studies (71). We further validated the EcR-RNAi line (BL29374; EcR RNAi 3) by ecdysone feeding and confirmed that its expression suppressed the ecdysone-induced (5 mM) increase in PH3-positive cells in the gut (SI Appendix, Fig. S2A), as explained previously (19) (A). All experiments involving EcR knockdown were performed using the RNAi line labeled as EcR-RNAi 3 in SI Appendix, Fig. S2A. All experimental lines were backcrossed into the w¹¹¹⁸ background for consistency. w¹¹¹⁸ line was used as the control strain due to its widespread use in Drosophila research, although the white gene has been implicated in regulating intestinal stem cell homeostasis during aging (72). Our experiments were conducted on young adult flies (6 to 10 d old), a stage at which age-associated white-dependent effects are not prominent (72). At the onset of mating, unmated females were transferred to new vials with food and mated at 25 °C for 48 h with an equivalent number of adult wild-type w¹¹¹⁸ males that were between 3 to 7 d old at 25 °C to maximize fecundity. After 48 h of mating, the males were discarded and the females were used for midgut dissection for all assays except the FACS assays. We did not clear the midguts of food prior to dissection, because we wanted to avoid interfering with metabolism by changing the diet (or starving the flies) prior to sample collection. However we did assay food amounts in the midguts during many experiments using a food-borne dye, and we believe the contribution of luminal food and microbiota to the total gut composition is minor. For the FACS assays (Fig. 1 H and I), flies were mated for 5 d before dissection (at 9 d posteclosion) in order to assay final nuclear ploidies and numbers after mating-dependent adaptive growth was complete.

Flow Cytometry.

For nucleus counting by flow cytometry, we used a mating protocol that differed from the rest of the study. Unmated D. melanogaster females (5 d posteclosion, 25 °C) were mated with an equal number of w¹¹¹⁸ males for 5 d, alongside age- and genotype-matched unmated controls. The longer mating period (5 d vs. 2 d for metabolomics and transcriptomics experiments) was used to discern final, endpoint effects on cell growth and proliferation, since cell numbers and ploidy increase cumulatively. On day 10 posteclosion, 25 midguts, per sample were dissected for nuclear isolation and flow cytometry as described (SI Appendix, Materials and Methods).

GC-MS Metabolomics and LC–MS Lipidomics.

Flies were dissected in ice-cold PBS, and midguts were flash-frozen in liquid nitrogen. For each experiment, 60 or 40 midguts were collected for each replicate for metabolomics or lipidomics, respectively. Fecal samples were collected after culturing 40 to 70 flies on lab-made food for 24 h. Feces were scraped with a dampened cotton swab (avoiding food), suspended in 300 MilliQ water. For metabolomics using GC-MS, samples were homogenized in 450 µL of chilled 90% methanol with d4-succinic acid using a ceramic beadmill (Qiagen, #13116-50) and OMNI Bead Ruptor 24, followed by a 1-h incubation at –20 °C. After centrifugation (20,000× g, 10 min, 4 °C), 400 µL supernatant was transferred to tubes containing d27-myristic acid. Quality control samples were pooled from each extract, and blanks were processed identically. Samples were dried under vacuum and analyzed by GC-MS (Agilent 5977b GC-MS MSD-HES fitted with an Agilent 7693A automatic liquid sampler). Dried extracts were reconstituted in 40 µL of 40 mg/mL MOX in dry pyridine, incubated at 37 °C for 1 h, and derivatized with 60 µL MSTFA + 1% TMCS at 37 °C for 30 min. After shaking, 1 µL was injected (split mode, 250 °C inlet). Most metabolites used a 10:1 split; saturated ones used 50:1. Separation was performed on a 30 m Agilent Zorbax DB-5MS with a 10 m Duraguard capillary, using helium at 1 mL/min.

For lipid metabolomics (“lipidomics”) by LC–MS, lipid extraction followed the protocol of Matyash et al. (73). We used a biphasic solvent system of cold methanol, methyl tert-butyl ether (MTBE), and water with some modifications. In a randomized sequence, 225 µL MeOH each was added to each sample with internal standards. The samples were homogenized for 30 s, transferred to microcentrifuge tubes (polypropylene 1.7 mL, VWR, USA) with 750 µL MTBE, and then incubated on ice with occasional vortexing for 1 h. After incubation period, the samples were centrifuged at 15,000× g for 10 min at 4 °C. The organic (upper) layer was collected, and the aqueous (lower) layer was re-extracted with 1 mL of 10:3:2.5 (v/v/v) MTBE/MeOH/dd-H2O, briefly vortexed, incubated at RT, and centrifuged at 15,000× g for 10 min at 4 °C. Upper phases were combined and evaporated to dryness under speedvac. Lipid extracts were reconstituted in 400 µL of 4:1:1 (v/v/v) IPA/ACN/water and transferred to an LC–MS vial for analysis. Concurrently, a process blank sample was prepared and pooled quality control (QC) samples were prepared by taking equal volumes from each sample after final resuspension. Lipid extracts were separated using an Acquity UPLC CSH C18 column (2.1 × 100 mm, 1.7 µm) with a VanGuard precolumn, maintained at 65 °C, and analyzed using an Agilent 1290 UPLC coupled to an Agilent 6545 Q-TOF dual AJS-ESI mass spectrometer. Samples were run in randomized order under both positive and negative ionization modes (scan range m/z 100 to 1,700). Source conditions differed slightly: positive mode used 225 °C gas temp and 40 psig nebulizer pressure; negative mode used 300 °C and 30 psig, with other parameters constant. Mobile phase A was ACN:H₂O (60:40) and B was IPA:ACN:H₂O (90:9:1), both with 10 mM ammonium formate + 0.1% formic acid; for negative mode, modifiers were replaced with 10 mM ammonium acetate. The gradient increased from 15 to 99% B over 13.8 min, held, then returned to baseline, with a total runtime of ~21.7 min. Flow rate was 0.4 mL/min with injection volumes of 1 µL (positive) and 10 µL (negative). MS/MS used iterative exclusion with collision energies of 20 V (positive) and 27.5 V (negative).

LC–MS and GC–MS Data Processing.

A comprehensive methodology was applied for data processing, including the use of the Agilent MassHunter (MH) workstation and the MH Qualitative and MH Quantitative software packages. To ensure the reliability of our metabolites and lipids dataset, pooled quality control samples (n = 8) and blanks (n = 4) were systematically integrated into the samples list. Lipid annotation was performed using precise mass and MS/MS correspondence using the Agilent Lipid Annotator library and LipidMatch (as described below). Lipid Annotator-derived results for both positive and negative ionization modalities were merged based on classified lipid identification. Metabolite identity was established using a combination of an in-house metabolite library developed using pure purchased standards, the NIST library, and the Fiehn library. Subsequently, the data extracted from MH Quantitative data were subjected to a review in Excel, where the initial lipid and metabolite targets were examined according to established criteria. Only lipids with relative SD (RSD) of less than 30% within the QC samples were used for further investigation. In addition, only lipids with background AUC values in blank samples that were less than 30% of those found in the QC samples were included in the analysis. For GC-MS identified metabolites, only metabolites with a % Coefficient of Variation <30% were retained for further statistical analysis. The organized data were then normalized using class-specific internal standards and aggregation, giving the “MetaboAnalyst input data” sets included in Dataset S1, and used for subsequent statistical analysis as described below.

Statistical Analysis of Metabolomics and Lipidomics data.

Lipid and metabolite peak data that were prefiltered as described above (shown in Dataset S1) were further analyzed using the MetaboAnalyst software platform for graphical data comparisons (heatmaps, volcano plots, metabolite set and class enrichment graphs, etc). Before performing statistical analysis with MetaboAnalyst, metabolite and lipid values were subjected to a log10 transformation. Values corresponding to each metabolite were also standardized by centering on the mean and normalizing them by the square root of their respective SD (i.e., Pareto scaling.). Statistical analysis and graphical output was then performed, using sum normalization to remove effects due to changes in gut size between samples. Log2-fold changes as cited in the text and shown in SI Appendix, Fig. S5 were calculated on the basis of unprocessed peak values. Additional analysis was performed using other software. Metabolite set enrichment analyses displayed as bubble plots (Figs. 2A and 6 A and B) were generated using custom code and the R package ggplot2. Compound class plots (Figs. 2B and 7B) were generated using custom analysis tools available on Github at: https://github.com/mmarchetti90/metabolomics_lipidomics. Metabolite heat maps (Figs. 4D and 7A and SI Appendix, Fig. S6C) were generated using the heatmap.2 function from the R package gplots (https://cran.r-project.org/package=gplots). Raw values were converted to size-normalized peak intensities, z-score normalized, manually grouped and ordered, and plotted with unsupervised clustering.

For additional details about Drosophila stocks and transgenes, Drosophila media, Flow Cytometry, Protein and Carbohydrate assays, RNA sequencing, and RNA sequence data analysis, please see the SI Appendix, Materials and Methods. See SI Appendix, Figs. S1–S6.

Supplementary Material

Appendix 01 (PDF)

Dataset S01 (XLSX)

Dataset S02 (XLSX)

Dataset S03 (XLSX)

Dataset S04 (XLSX)

Dataset S05 (XLSX)

Data, Materials, and Software Availability

Raw RNA sequence data are available at the NCBI Gene Expression Omnibus repository at (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE315594 (33). All other study data are included in the article and/or supporting information.