Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Response of the microbiome–gut–brain axis in Drosophila to amino acid deficit

Abstract

A balanced intake of macronutrients—protein, carbohydrate and fat—is essential for the well-being of organisms. An adequate calorific intake but with insufficient protein consumption can lead to several ailments, including kwashiorkor1. Taste receptors (T1R1–T1R3)2 can detect amino acids in the environment, and cellular sensors (Gcn2 and Tor)3 monitor the levels of amino acids in the cell. When deprived of dietary protein, animals select a food source that contains a greater proportion of protein or essential amino acids (EAAs)4. This suggests that food selection is geared towards achieving the target amount of a particular macronutrient with assistance of the EAA-specific hunger-driven response, which is poorly understood. Here we show in Drosophila that a microbiome–gut–brain axis detects a deficit of EAAs and stimulates a compensatory appetite for EAAs. We found that the neuropeptide CNMamide (CNMa)5 was highly induced in enterocytes of the anterior midgut during protein deprivation. Silencing of the CNMa–CNMa receptor axis blocked the EAA-specific hunger-driven response in deprived flies. Furthermore, gnotobiotic flies bearing an EAA-producing symbiotic microbiome exhibited a reduced appetite for EAAs. By contrast, gnotobiotic flies with a mutant microbiome that did not produce leucine or other EAAs showed higher expression of CNMa and a greater compensatory appetite for EAAs. We propose that gut enterocytes sense the levels of diet- and microbiome-derived EAAs and communicate the EAA-deprived condition to the brain through CNMa.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Amino acid deprivation promotes the compensatory EAA appetite independently of taste and stimulates CNMa expression in the gut.
Fig. 2: Intestinal CNMa and neuronal CNMaR comprising the gut–brain axis promote the compensatory EAA appetite.
Fig. 3: The gut microbiome regulates the compensatory EAA appetite.

Similar content being viewed by others

Data availability

The original data for the immunoblotting are shown in Supplementary Fig. 1. All other raw data are available from corresponding authors on request. Source data are provided with this paper.

References

  1. Müller, O. & Krawinkel, M. Malnutrition and health in developing countries. CMAJ 173, 279–286 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Nelson, G. et al. An amino-acid taste receptor. Nature 416, 199–202 (2002).

    Article  CAS  PubMed  ADS  Google Scholar 

  3. Efeyan, A., Comb, W. C. & Sabatini, D. M. Nutrient-sensing mechanisms and pathways. Nature 517, 302–310 (2015).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  4. Simpson, S. J., Le Couteur, D. G. & Raubenheimer, D. Putting the balance back in diet. Cell 161, 18–23 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Jung, S.-H. et al. Identification of a novel insect neuropeptide, CNMa and its receptor. FEBS Lett. 588, 2037–2041 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. Ganguly, A. et al. A molecular and cellular context-dependent role for Ir76b in detection of amino acid taste. Cell Rep. 18, 737–750 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Croset, V., Schleyer, M., Arguello, J. R., Gerber, B. & Benton, R. A molecular and neuronal basis for amino acid sensing in the Drosophila larva. Sci. Rep. 6, 34871 (2016).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  8. Nottebohm, E. et al. The gene poxn controls different steps of the formation of chemosensory organs in Drosophila. Neuron 12, 25–34 (1994).

    Article  CAS  PubMed  Google Scholar 

  9. Dus, M. et al. Nutrient sensor in the brain directs the action of the brain–gut axis in Drosophila. Neuron 87, 139–151 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yang, Z. et al. A post-ingestive amino acid sensor promotes food consumption in Drosophila. Cell Res. 28, 1013–1025 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Buchon, N. et al. Morphological and molecular characterization of adult midgut compartmentalization in Drosophila. Cell Rep. 3, 1725–1738 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. Masuyama, K., Zhang, Y., Rao, Y. & Wang, J. W. Mapping neural circuits with activity-dependent nuclear import of a transcription factor. J. Neurogenet. 26, 89–102 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gallinetti, J., Harputlugil, E. & Mitchell, J. R. Amino acid sensing in dietary-restriction-mediated longevity: roles of signal-transducing kinases GCN2 and TOR. Biochem. J. 449, 1–10 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Dong, J., Qiu, H., Garcia-Barrio, M., Anderson, J. & Hinnebusch, A. G. Uncharged tRNA activates GCN2 by displacing the protein kinase moiety from a bipartite tRNA-binding domain. Mol. Cell 6, 269–279 (2000).

    Article  CAS  PubMed  Google Scholar 

  15. Wolfson, R. L. & Sabatini, D. M. The dawn of the age of amino acid sensors for the mTORC1 pathway. Cell Metab. 26, 301–309 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ye, J. et al. The GCN2-ATF4 pathway is critical for tumour cell survival and proliferation in response to nutrient deprivation. EMBO J. 29, 2082–2096 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Roczniak-Ferguson, A. et al. The transcription factor TFEB links mTORC1 signaling to transcriptional control of lysosome homeostasis. Sci. Signal. 5, ra42 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Bouché, V. et al. Drosophila Mitf regulates the V-ATPase and the lysosomal-autophagic pathway. Autophagy 12, 484–498 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Leitão-Gonçalves, R. et al. Commensal bacteria and essential amino acids control food choice behavior and reproduction. PLoS Biol. 15, e2000862 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Shin, S. C. et al. Drosophila microbiome modulates host developmental and metabolic homeostasis via insulin signaling. Science 334, 670–674 (2011).

    Article  CAS  PubMed  ADS  Google Scholar 

  21. Erkosar, B., Storelli, G., Defaye, A. & Leulier, F. Host-intestinal microbiota mutualism: “learning on the fly”. Cell Host Microbe 13, 8–14 (2013).

    Article  CAS  PubMed  Google Scholar 

  22. Sun, J. et al. Drosophila FIT is a protein-specific satiety hormone essential for feeding control. Nat. Commun. 8, 14161 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  23. Liu, Q. et al. Branch-specific plasticity of a bifunctional dopamine circuit encodes protein hunger. Science 356, 534–539 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  24. Bjordal, M., Arquier, N., Kniazeff, J., Pin, J. P. & Léopold, P. Sensing of amino acids in a dopaminergic circuitry promotes rejection of an incomplete diet in Drosophila. Cell 156, 510–521 (2014).

    Article  CAS  PubMed  Google Scholar 

  25. Hao, S. et al. Uncharged tRNA and sensing of amino acid deficiency in mammalian piriform cortex. Science 307, 1776–1778 (2005).

    Article  CAS  PubMed  ADS  Google Scholar 

  26. Gribble, F. M. & Reimann, F. Enteroendocrine cells: chemosensors in the intestinal epithelium. Annu. Rev. Physiol. 78, 277–299 (2016).

    Article  CAS  PubMed  Google Scholar 

  27. Gribble, F. M. & Reimann, F. Function and mechanisms of enteroendocrine cells and gut hormones in metabolism. Nat. Rev. Endocrinol. 15, 226–237 (2019).

    Article  CAS  PubMed  Google Scholar 

  28. Marianes, A. & Spradling, A. C. Physiological and stem cell compartmentalization within the Drosophila midgut. eLife 2, e00886 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lemaitre, B. & Miguel-Aliaga, I. The digestive tract of Drosophila melanogaster. Annu. Rev. Genet. 47, 377–404 (2013).

    Article  CAS  PubMed  Google Scholar 

  30. Kiela, P. R. & Ghishan, F. K. Physiology of intestinal absorption and secretion. Best Pract. Res. Clin. Gastroenterol. 30, 145–159 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Redhai, S. et al. An intestinal zinc sensor regulates food intake and developmental growth. Nature 580, 263–268 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  32. Hill, C. M., Berthoud, H.-R., Münzberg, H. & Morrison, C. D. Homeostatic sensing of dietary protein restriction: a case for FGF21. Front. Neuroendocrinol. 51, 125–131 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Fisher, F. M. & Maratos-Flier, E. Understanding the physiology of FGF21. Annu. Rev. Physiol. 78, 223–241 (2016).

    Article  CAS  PubMed  Google Scholar 

  34. De Sousa-Coelho, A. L., Marrero, P. F. & Haro, D. Activating transcription factor 4-dependent induction of FGF21 during amino acid deprivation. Biochem. J. 443, 165–171 (2012).

    Article  PubMed  Google Scholar 

  35. Zhang, Y. et al. TFEB-dependent induction of thermogenesis by the hepatocyte SLC2A inhibitor trehalose. Autophagy 14, 1959–1975 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Fon Tacer, K. et al. Research resource: comprehensive expression atlas of the fibroblast growth factor system in adult mouse. Mol. Endocrinol. 24, 2050–2064 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Arrese, E. L. & Soulages, J. L. Insect fat body: energy, metabolism, and regulation. Annu. Rev. Entomol. 55, 207–225 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hadjieconomou, D. et al. Enteric neurons increase maternal food intake during reproduction. Nature 587, 455–459 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  39. Wang, P., Jia, Y., Liu, T., Jan, Y. N. & Zhang, W. Visceral mechano-sensing neurons control drosophila feeding by using Piezo as a sensor. Neuron 108, 640–650 (2020).

    Article  CAS  PubMed  Google Scholar 

  40. Semba, R. D. et al. Child stunting is associated with low circulating essential amino acids. EBioMedicine 6, 246–252 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Simpson, S. J. & Raubenheimer, D. Obesity: the protein leverage hypothesis. Obes. Rev. 6, 133–142 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. Venken, K. J. T. et al. MiMIC: a highly versatile transposon insertion resource for engineering Drosophila melanogaster genes. Nat. Methods 8, 737–743 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kondo, S. & Ueda, R. Highly improved gene targeting by germline-specific Cas9 expression in Drosophila. Genetics 195, 715–721 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Dus, M., Ai, M. & Suh, G. S. B. Taste-independent nutrient selection is mediated by a brain-specific Na+/solute co-transporter in Drosophila. Nat. Neurosci. 16, 526–528 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ryu, J.-H. et al. Innate immune homeostasis by the homeobox gene Caudal and commensal-gut mutualism in Drosophila. Science 319, 777–782 (2008).

    Article  CAS  PubMed  ADS  Google Scholar 

  46. Tasanapak, K., Masud-Tippayasak, U., Matsushita, K., Yongmanitchai, W. & Theeragool, G. Influence of Acetobacter pasteurianus SKU1108 aspS gene expression on Escherichia coli morphology. J. Microbiol. 51, 783–790 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. Katzen, F., Becker, A., Ielmini, M. V., Oddo, C. G. & Ielpi, L. New mobilizable vectors suitable for gene replacement in gram-negative bacteria and their use in mapping of the 3′ end of the Xanthomonas campestris pv. campestris gum operon. Appl. Environ. Microbiol. 65, 278–282 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the W.-J.L. and G.S.B.S. laboratory members for discussion and critical reading of the manuscript, and we thank the KAIST Biocore center (operator: J. Kim). This work is supported by grants from the Samsung Science and Technology Foundation (project number: SSTF-BA-1802-11) and the National Research Foundation of Korea (NRF-2020R1A2C2009865); by NIH R01 grants (R01DK116294 and R01DK106636, which have been transferred to H. Don Ryoo at New York University) to G.S.B.S; and by grants from National Creative Research Initiative programs of the National Research Foundation of South Korea (2015R1A3A2033475) and the Samsung Science and Technology Foundation (project number: SSTF-BA-1401-15) to W.-J.L. B.K. is supported by the National Research Foundation of South Korea (NRF-2020R1I1A1A01072255).

Author information

Authors and Affiliations

Authors

Contributions

B.K. and M.I.K. conceived, designed, performed and analysed the experiments. Y.O., M.K., E.-K.K., I.-H.J., J.-H.L. and S.-G.K. performed the experiments. G.S.B.S. and W.-J.L. conceived and supervised the project and designed and analysed the experiments. G.S.B.S., W.-J.L. and B.K. wrote the manuscript.

Corresponding authors

Correspondence to Greg S. B. Suh or Won-Jae Lee.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Catherine Schretter and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Compensatory appetite for EAAs in amino-acid-deprived male flies, virgin female flies, poxn-mutant flies and mated female flies in which Ir76b+ neurons or Dh44+ neurons were inactivated.

ac, Two-choice preferences of wild-type w1118 mated female (a), male (b) and virgin female (c) flies that had been fed (−) or had been deprived of amino acids for the indicated durations (5, 24, 48 and 72 h). Flies were given a choice between: l-EAA + l-NEAA + d-glucose and d-EAA + d-NEAA + d-glucose (a) or l-EAA + d-glucose and d-EAA + d-glucose (b, c). d, Food preferences of w1118 mated female flies fed with diets containing different amounts of dietary yeast were given a choice between l-EAA + d-glucose and d-EAA + d-glucose. e, Food preferences of flies in which Ir76b+ neurons had been inactivated by expressing tetanus toxin (TNT) (Ir76b-LexA>LexAop-TNT flies) were fed (−) or were deprived of amino acids for 48 h before the two-choice assay: l-EAA + d-glucose versus d-EAA + d-glucose. Flies carrying Ir76b-LexA alone or LexAop-TNT alone were used as controls. f, Two-choice preferences of control w1118 and poxn−/− flies that had been deprived of amino acids for 48 h. g, Two-choice preferences of flies carrying Dh44-Gal4 and UAS-Kir2.1 that had been fed (−) or had been deprived of amino acids for 48 h. Flies carrying Dh44-Gal4 alone or UAS-Kir2.1 alone were used as controls. Inactivation of Dh44+ neurons was achieved by expressing inwardly rectifying potassium channels (Kir2.1) in Dh44+ neurons. Data are mean ± s.e.m. P values are indicated; unpaired two-tailed t-test in a; one-way ANOVA with Tukey’s post-hoc test in bg. n is experimental trials. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 2 Amino acid deprivation enhances the expression of CNMa in enterocytes, but not in intestinal stem cells, enteroblasts or enteroendocrine cells.

a, Normalized CNMa mRNA expression levels measured by qPCR in flies that were fed isocaloric diets containing varying amounts of dietary yeast for 5–6 days (n = 5). b, c, CNMa promoter activity in the gut of CNMa-GAL4>UAS-GFP flies that were fed an isocaloric diet containing 2% (low-amino-acid diet) versus 10% (high-amino-acid diet) of yeast for 7 days. Representative confocal images of the whole gut (b) and quantifications of the GFP fluorescence in the R2 segment of the anterior midgut (c) are shown. d, Representative confocal images showing enterocytes in the anterior R2 midgut that express CNMa. Intestinal stem cells (ISCs) and enteroblasts (EBs) were respectively marked by β-galactose (β-gal) staining of the gut in flies carrying Delta-lacZ (red), CNMa-Gal4 and UAS-GFP (green) (top left), and in flies bearing Su(H)-lacZ (red), CNMa-Gal4 and UAS-GFP (green) (top middle). Enteroendocrine cells (EEs) are labelled by anti-prospero antibody staining (red) (top right), whereas enterocytes (ECs) are identified on the basis of their large polyploidy nuclei as revealed by DAPI staining (blue). In all cases, CNMa expression was visualized by GFP (green). A schematic representation of different intestinal cell types is shown. e, f, Representative confocal images of enterocytes in the R2 (e) and R4 (f) midgut regions of a fly carrying NP1-Gal4 (enterocyte-specific driver) and UAS-CD8-GFP co-labelled with anti-GFP (green) and anti-CNMa (red) antibodies. Nuclei are stained with DAPI (blue). Scale bars, 200 μm (b); 50 μm (c); 10 μm (df). Single-plane images are shown. Representative images are selected from at least 20 independent samples collected in each experiment. Data are mean ± s.e.m. P values are indicated; one-way ANOVA with Tukey’s post-hoc test in a; unpaired two-tailed t-test in c. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 3 Amino acid deprivation has no effect on CNMa expression in the fat body or the brain, whereas EAA deprivation but not NEAA deprivation influences CNMa expression in the gut.

a, b, Representative confocal images (left), the relative signal intensity of native GFP fluorescence (middle) and the numbers of GFP-positive cells (right) in the fat body (a) and the brain (b; insets show the dorsal region) in flies carrying CNMa-Gal4 and UAS-GFP (green) that were fed a high-amino-acid versus a low-amino-acid diet. Nuclei in the fat body counterstained with DAPI (a, left), and the brain stained with anti-GFP antibody (green) and the neuropil marker nc82 (magenta) (b, left) are shown. The numbers of GFP-positive cells are as follows: 41.00 ± 7.28 (high amino acids) and 41.54 ± 8.16 (low amino acids) in the fat body; 3.96 ± 1.48 (high amino acids) and 3.29 ± 1.33 (low amino acids) in the brain. Scale bars, 50 μm (a, b); 10 μm (b, inset). c, d, EAA deprivation, but not NEAA deprivation, induced CNMa expression (c) and possibly mobilized intracellular calcium (d). Quantifications of GFP fluorescence in the R2 region of the anterior midgut in CNMa-GAL4>UAS-GFP flies (c) or CNMa-GAL4>CaLexA flies (d) that were fed with an EAA-deficient versus a NEAA-deficient diet for two days. e, f, Deficiency of a single EAA in a diet induced CNMa expression (e) and possibly mobilized intracellular calcium (f). Quantifications of GFP fluorescence in the R2 region in CNMa-GAL4>UAS-GFP flies (e) or CNMa-GAL4>CaLexA flies (f) that were fed with a holidic diet lacking a single EAA for three days. Data are mean ± s.e.m. P values are indicated; unpaired two-tailed t-test in a, b; one-way ANOVA with Tukey’s post-hoc test in cf. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 4 Molecular characterization of CNMa and CNMaR knockout lines.

a, b, The genomic loci of CNMa (a) and CNMaR (b) before and after the deletions were generated. The open reading frames and the cleavage sites used by gRNAs are indicated by yellow boxes and arrowheads, respectively. The gRNA-matching sequences are denoted in bold. Deleted regions were confirmed by sequencing of the genomic DNA; 20 base pairs (AGGAAGGAAGGCGATGGATT) and 2 base pairs (AC) were inserted in the deletion region of CNMa and CNMaR loci, respectively. c, The PCR analyses confirmed the lack of CNMa and CNMaR transcripts in CNMa−/− and CNMaR−/− flies, respectively. Representative images were selected from three independent samples collected in each experiment.

Source data

Extended Data Fig. 5 The activities of Tor and Gcn2 signalling pathways modulated by EAA deprivation regulate CNMa expression in the gut, but have no effect on CNMa expression in the brain or fat body.

a, Two-choice behavioural preferences of amino-acid-deprived flies in which UAS-CNMaRNAi had been expressed specifically in the enterocytes (NP1-Gal4), fat body (Cg-Gal4) or neurons (Nsyb-Gal4). Flies carrying tissue-specific GAL4 alone were used as controls. b, c, Western blot analysis of phosphorylated eIF2α (p-eIF2α) and phosphorylated ribosomal protein S6K (p-S6K) in whole-gut lysates collected from mated female flies (around 5–6-days old) that were deprived of EAA (−EAA) for 48 h (b). The intensity of each band corresponding to phosphorylated eIF2α and S6K was quantified using the ImageJ automated digitizing program (NIH) (c). Results from three independent experiments were normalized against those in control flies, the average of which is arbitrarily set as 1. d, Quantifications of GFP fluorescence in the R2 region of the anterior midgut of CNMa-Gal4>UAS-GFP flies (control) or control flies carrying either UAS-mRFP, UAS-ninaBRNAi, UAS-Gcn2RNAi, UAS-Atf4RNAi, UAS-TorWT or UAS-MitfRNAi. e, f, Levels of CNMa expression in the brain or fat body of flies carrying CNMa-Gal4 and UAS-GFP that also harboured either UAS-TorWT or UAS-Gcn2RNAi. GFP signal intensities in the fat body (e) or brain (f) were measured by the native GFP fluorescence. Data are mean ± s.e.m. P values are indicated; unpaired two-tailed t-test in a, c; one-way ANOVA with Tukey’s post-hoc test in df. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 6 Enhancement of the CNMa promoter activity by co-expression of Atf4 and Mitf.

The 5′-flanking region (−1573/+1) of the CNMa gene was used to generate a pGL3-CNMa reporter plasmid. Drosophila S2 cells were transfected with the pGL3-CNMa reporter plasmid with pPac-Atf4 (Atf4), pPac-Mitf (Mitf) or both (Atf4 + Mitf). Luciferase activities were measured at 48 h after transfection. The luciferase activity of the pGL3-CNMa reporter co-transfected with an empty pPac vector was arbitrarily set to 1. The relative luciferase activities are shown as the mean ± s.e.m. from three independent experiments. P values are indicated (one-way ANOVA with Tukey’s post-hoc test). Statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 7 CNMaR-expressing neurons are located in the anterior midgut and the brain and are not overlapped with Ir76b+ neurons, and some respond to amino acid deprivation.

a, b, Representative confocal images of the anterior midgut of an adult fly carrying CNMaR-Gal4 and UAS-CD8-GFP that were co-labelled with anti-GFP antibody (green) and DAPI (blue) (a), and the brain of an adult fly carrying Ir76b-Gal4>UAS-CD8-GFP and CNMaR-LexA>LexAop-tdTomato, probed with anti-GFP (green) and anti-DsRed (red) antibodies, illustrate two populations of neuronal processes: one from Ir76b+ taste sensory neurons and another from CNMaR+ central nervous system (CNS) neurons (b). c, Measurements of calcium mobilization by CaLexA reporter (green) in mated female flies carrying CNMaR-Gal4>UAS-CaLexA (flies of around 2 days old maintained for 5 days on a high-amino-acid diet containing 10% dietary yeast) that were subjected to amino acid deprivation by transferring half of the flies to an agar medium containing 100mM d-glucose only for 48 h (right, protein deprivation) or that continued on the high-amino-acid diet (left, no deprivation). Arrowheads denote the enhancement of GFP intensity in the ellipsoid body (right). Scale bars, 200 μm (a); 50 μm (b, c). Z-stacked projection images are shown. Representative images were selected from at least five independent samples collected in each experiment.

Source data

Extended Data Fig. 8 Commensal bacteria influence CNMa expression in the gut, but not in the fat body or brain.

a, Quantifications of GFP fluorescence in the R2 region of the gut of conventionally reared and GF female flies carrying CNMa-Gal4>UAS-GFP fed on 10% or 15% dietary yeast. b, c, The level of CNMa expression in the fat body (b) or the brain (c) of flies bearing CNMa-Gal4 and UAS-GFP that had been reared in 10% dietary yeast were quantified using the GFP signal intensity measured by its native GFP fluorescence. d, Quantifications of GFP fluorescence in the R2 region of GF flies that had been mono-associated with A. pomorum or L. plantarum WJL. Data are mean ± s.e.m. P values are indicated; one-way ANOVA with Tukey’s post-hoc test in a, d; unpaired two-tailed t-test in b, c. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 9 Acetobacter colonization results in a significant increase in the amino acid absorption of the host and the suppression of the l-EAA preference through CNMaR-expressing neurons.

a, Levels of ingested deuterium-labelled amino acids (l-leucine-5,5,5-d3, l-phenyl-d5-alanine-2,3,3-d3 or l-glutamic acid-2,3,3,4,4-d5) in the haemolymph of GF control flies (−) fed on 5% sucrose alone and in the haemolymph of treated GF flies (+) fed on 5% sucrose containing deuterium-labelled amino acids (n = 3). b, Two-choice preferences of GF flies or GF flies that had been mono-associated with A. pomorum in which CNMaR+ neurons were conditionally activated by the heat-inducible TrpA1 at 30 °C. Note that a significantly higher bacterial load (approximately 10 times higher number of colony-forming units) of intestinal A. pomorum was found in flies maintained at 30 °C than in flies maintained at 22 °C in which control experiments were conducted (data not shown). GF-Aceto, GF flies mono-associated with A. pomorum; GF-Lacto, GF flies mono-associated with L. plantarum WJL. Data are mean ± s.e.m. P values are indicated; one-way ANOVA with Tukey’s post-hoc test in a, b. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Extended Data Fig. 10 CNMa expression and l-EAA preference are regulated by the microbiome and Tor signalling in the gut.

a, Quantifications of GFP fluorescence in the R2 region of the gut of GF flies carrying CNMa-Gal4>UAS-GFP that had been mono-associated with Acetobacter that has a mutation in the proC gene (AcetoΔproC) or the leuB gene (AcetoΔleuB). Complementation of the AcetoΔleuB strain was achieved by re-introducing the leuB gene to generate AcetoΔleuB_leuB. Dietary complementation of AcetoΔleuB was achieved by adding 10 mM leucine to the diet. b, c, Representative confocal images (left) and quantifications of GFP fluorescence (right) in the R2 region of the gut (b) and two-choice preferences (c) of GF flies that had been mono-associated with Acetobacter that has a mutation in ilvA (AcetoΔilvA). Dietary complementation of AcetoΔilvA was achieved by adding 10 mM isoleucine to the diet. GF flies carrying CNMa-Gal4>UAS-GFP and GF w1118 flies were used in b and c, respectively. d, Quantifications of GFP fluorescence in the R2 region of the gut of GF flies carrying CNMa-Gal4>UAS-GFP that had been mono-associated with an engineered strain of L. plantarum WJL that is capable of producing BCAAs (LactoBCAA). Dietary complementation of L.plantarum WJL (LactoWT) was achieved by adding 10 mM of leucine, isoleucine and valine to the diet (LactoWT + BCAA). e, Representative confocal images (left) and quantifications of the GFP signal (right) in the anterior R2 midgut region of AcetoΔleuB mono-associated GF flies carrying CNMa-Gal4 and UAS-GFP (GFcontrol), and flies carrying CNMa-Gal4, UAS-GFP and UAS-TorWT (GFTor-WT) on 10% dietary yeast, measured by the native GFP fluorescence. f, Two-choice preferences of AcetoΔleuB mono-associated flies carrying enterocyte-specific NP1-Gal4 (control), and flies carrying NP1-Gal4 and UAS-TorWT (n = 20). Nuclei were stained with DAPI. Scale bars, 50 μm (b, e). Data are mean ± s.e.m. P values are indicated; one-way ANOVA with Tukey’s post-hoc test in ad; unpaired two-tailed t-test in e, f. Sample sizes and statistical analyses are shown in Supplementary Table 1.

Source data

Supplementary information

Supplementary Figure 1

Uncropped images of Western blot (related to Extended Data Figure 5b).

Reporting Summary

Supplementary Tables

This file contains Supplementary Tables 1-4. Supplementary Table 1 contains detailed descriptions of the experimental conditions, sample sizes, and statistical analyses that were used in this study. Supplementary Table 2 contains food sources for two choice assay that were used in this study. Supplementary Table 3 contains real-time qPCR primer sequences that were used in this study (related to Figure 1d and Extended Data Figure 2a). Supplementary Table 4 contains PCR primer sequences that were used in this study (related to Extended Data Figure 4c).

Peer Review File

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, B., Kanai, M.I., Oh, Y. et al. Response of the microbiome–gut–brain axis in Drosophila to amino acid deficit. Nature 593, 570–574 (2021). https://doi.org/10.1038/s41586-021-03522-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-021-03522-2

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing