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Transcriptional responses in feeder time-trained foragers suggest diverse interactions between the circadian clock and mushroom bodies in honey bees

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Abstract

A hundred years ago Karl von Frisch and his students demonstrated that honey bees use time-memory to schedule their daily foraging flights. However, till today little is known about molecular processes and functional interactions between memory centers and the circadian clock underlying the capability to form time-memories in animals. Combining feeder time-training of foragers with time-series RNA sequencing and RNAscope labeling revealed molecular features associated with the expectation of foraging activity: (i) anticipatory activation of the transcription factor Egr1 and the receptor for pigment dispersing factor (pdfr) in the small-type Kenyon cells (KCs), (ii) synchronized peak-expression of more than 850 genes including Egr1 downstream genes and well-known memory-related genes during training time, and (iii) groups of KCs and cells associated with the central complex co-expressing per and cry2. With respect to earlier studies characterizing behavioral correlates of time-memory, we speculate that anticipatory initiation of physiological and transcriptional activity in the small-type KCs might function in preparing the worker bee for its foraging activity including reactivation and reconsolidation of foraging related memories. The expression of clock genes in addition to pdfr in KCs suggests an unexpected complexity of functional interactions between memory centers and the clock in honey bees.

Data availability

The RNA-seq data generated and/or analyzed during the current study have been deposited in the Gene Expression Omnibus (GEO) under the Accession Number GSE263576.

References

  1. Beling, I. Über Das Zeitgedӓchtnis der Bienen. Z. F Vergl Physiologie. 9, 259–338. https://doi.org/10.1007/BF00340159 (1929).

    Google Scholar 

  2. Krebs, J. R. & Biebach, H. Time-Place Learning by Garden Warblers (Sylvia borin): Route or Map? Ethology 83, 248–256. (1989). https://doi.org/10.1111/j.1439-0310.1989.tb00532.x

  3. Van Der Zee, E. A. et al. Circadian Time-Place learning in mice depends on cry genes. Curr. Biol. 18, 844–848. https://doi.org/10.1016/j.cub.2008.04.077 (2008).

    Google Scholar 

  4. Chouhan, N. S., Wolf, R., Helfrich-Förster, C. & Heisenberg, M. Flies remember the time of day. Curr. Biol. 25, 1619–1624. https://doi.org/10.1016/j.cub.2015.04.032 (2015).

    Google Scholar 

  5. Sharma, V. K. Adaptive significance of circadian clocks. Chronobiol. Int. 20, 901–919. https://doi.org/10.1081/CBI-120026099 (2003).

    Google Scholar 

  6. Wahl, O. Neue untersuchungen über Das Zeitgedächtnis der Bienen. Z. F Vergl Physiologie. 16, 529–589. https://doi.org/10.1007/BF00338333 (1932).

    Google Scholar 

  7. Pahl, M., Zhu, H., Pix, W., Tautz, J. & Zhang, S. Circadian timed episodic-like memory – a bee knows what to do when,and also where. J. Exp. Biol. 210, 3559–3567. https://doi.org/10.1242/jeb.005488 (2007).

    Google Scholar 

  8. Kleber, E. Hat Das Zeitgedächtnis der Bienen biologische bedeutung ? Z. Vergl Physiol. 22, 221–262. https://doi.org/10.1007/BF00586500 (1935).

    Google Scholar 

  9. Koltermann, R. Periodicity in the activity and learning performance of the honeybee. In Experimental Analysis of Insect Behavior (Springer Berlin), 218–227. (1974).

  10. Page, T. L. Circadian regulation of learning and memory. Curr. Opin. Insect Sci. 7, 87–91. https://doi.org/10.1016/j.cois.2014.12.001 (2015).

    Google Scholar 

  11. Gallistel, C. R. The Organization of Learning (The MIT Press) 1990.

  12. Flyer-Adams, J. G. et al. Regulation of olfactory associative memory by the circadian clock output signal Pigment-Dispersing factor (PDF). J. Neurosci. 40, 9066–9077. https://doi.org/10.1523/JNEUROSCI.0782-20.2020 (2020).

    Google Scholar 

  13. Shah, A., Jain, R. & Brockmann, A. Egr-1: A candidate transcription factor involved in molecular processes underlying Time-Memory. Front. Psychol. 9, 865. https://doi.org/10.3389/fpsyg.2018.00865 (2018).

    Google Scholar 

  14. Beer, K. & Helfrich-Förster, C. Model and Non-model insects in chronobiology. Front. Behav. Neurosci. 14, 601676. https://doi.org/10.3389/fnbeh.2020.601676 (2020).

    Google Scholar 

  15. Van Nest, B. N., Otto, M. W. & Moore, D. High experience levels delay recruitment but promote simultaneous time-memories in honey bee foragers. J. Experimental Biology Jeb. 187336. https://doi.org/10.1242/jeb.187336 (2018).

  16. Singh, A. S., Shah, A. & Brockmann, A. Honey bee foraging induces upregulation of early growth response protein 1, hormone receptor 38 and candidate downstream genes of the ecdysteroid signalling pathway: Honey bee foraging upregulates Egr-1 and Hr38 genes. Insect Mol. Biol.. 27, 90–98. (2018). https://doi.org/10.1111/imb.12350

  17. Yap, E. L. & Greenberg, M. E. Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior. Neuron 100, 330–348. (2018). https://doi.org/10.1016/j.neuron.2018.10.013

  18. Khamis, A. M. et al. Insights into the transcriptional architecture of behavioral plasticity in the honey bee apis mellifera. Sci. Rep. 5, 11136. https://doi.org/10.1038/srep11136 (2015).

    Google Scholar 

  19. Alberini, C. M. & Kandel, E. R. The regulation of transcription in memory consolidation. Cold Spring Harb Perspect. Biol. 7, a021741. https://doi.org/10.1101/cshperspect.a021741 (2015).

    Google Scholar 

  20. Chandrasekaran, S. et al. Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states. Proc. Natl. Acad. Sci. U.S.A. 108, 18020–18025. https://doi.org/10.1073/pnas.1114093108 (2011).

  21. Jones, S. G., Nixon, K. C. J., Chubak, M. C. & Kramer, J. M. Mushroom Body Specific Transcriptome Analysis Reveals Dynamic Regulation of Learning and Memory Genes After Acquisition of Long-Term Courtship Memory in Drosophila. G3 Genes|Genomes|Genetics 8, 3433–3446. https://doi.org/10.1534/g3.118.200560 (2018).

  22. Shih, M. F. M., Davis, F. P., Henry, G. L. & Dubnau, J. Nuclear Transcriptomes of the Seven Neuronal Cell Types That Constitute the Drosophila Mushroom Bodies. G3 Genes|Genomes|Genetics 9, 81–94. https://doi.org/10.1534/g3.118.200726 (2019).

  23. Suenami, S., Oya, S., Kohno, H. & Kubo, T. Kenyon cell Subtypes/Populations in the honeybee mushroom bodies: possible function based on their gene expression Profiles, Differentiation, possible Evolution, and application of genome editing. Front. Psychol. 9, 1717. https://doi.org/10.3389/fpsyg.2018.01717 (2018).

    Google Scholar 

  24. Kandel, E. R., Koester, J., Mack, S. & Siegelbaum, S. (eds) Principles of Neural Science Sixth Edition (McGraw Hill), 2021).

  25. Hamilton, W. B. et al. Dynamic lineage priming is driven via direct enhancer regulation by ERK. Nature 575, 355–360. https://doi.org/10.1038/s41586-019-1732-z (2019).

    Google Scholar 

  26. Kornhauser, J. M., Nelson, D. E., Mayo, K. E. & Takahashi, J. S. Regulation of Jun -B messenger RNA and AP-1 activity by light and a circadian clock. Science 255, 1581–1584. https://doi.org/10.1126/science.1549784 (1992).

    Google Scholar 

  27. Jagannath, A. et al. The multiple roles of salt-inducible kinases in regulating physiology. Physiol. Rev. 103, 2231–2269. https://doi.org/10.1152/physrev.00023.2022 (2023).

    Google Scholar 

  28. Hirayama, J., Cardone, L., Doi, M. & Sassone-Corsi, P. Common pathways in circadian and cell cycle clocks: Light-dependent activation of Fos/AP-1 in zebrafish controls CRY-1a and WEE-1. Proc. Natl. Acad. Sci. U.S.A. 102, 10194–10199. https://doi.org/10.1073/pnas.0502610102 (2005).

  29. Iino, S. et al. Neural activity mapping of bumble bee (Bombus ignitus) brains during foraging flight using immediate early genes. Sci. Rep. 10, 7887. https://doi.org/10.1038/s41598-020-64701-1 (2020).

    Google Scholar 

  30. Kaneko, K., Suenami, S. & Kubo, T. Gene expression profiles and neural activities of Kenyon cell subtypes in the honeybee brain: identification of novel ‘middle-type’ Kenyon cells. Zool. Lett. 2, 14. https://doi.org/10.1186/s40851-016-0051-6 (2016).

  31. Kumar, S. et al. An ecdysone-responsive nuclear receptor regulates circadian rhythms in drosophila. Nat. Commun. 5, 5697. https://doi.org/10.1038/ncomms6697 (2014).

    Google Scholar 

  32. Scheiner, R. et al. Learning, gustatory responsiveness and tyramine differences across nurse and forager honeybees. J. Experimental Biology Jeb. 152496. https://doi.org/10.1242/jeb.152496 (2017).

  33. Peng, T., Derstroff, D., Maus, L., Bauer, T. & Grüter, C. Forager age and foraging state, but not cumulative foraging activity, affect biogenic amine receptor gene expression in the honeybee mushroom bodies. Genes Brain Behav. 20, e12722. https://doi.org/10.1111/gbb.12722 (2021).

    Google Scholar 

  34. Kandel, E. R., Dudai, Y. & Mayford, M. R. Learning and Memory (Cold Spring Harbor Laboratory Press), 2016).

  35. Galizia, C. G., Eisenhardt, D. & Giurfa, M. (eds) Honeybee Neurobiology and Behavior: A Tribute to Randolf Menzel (Springer Netherlands) https://doi.org/10.1007/978-94-007-2099-2 (2012).

  36. Kuwabara, T., Kohno, H., Hatakeyama, M. & Kubo, T. Evolutionary dynamics of mushroom body Kenyon cell types in hymenopteran brains from multifunctional type to functionally specialized types. Sci. Adv. 9, eadd4201. https://doi.org/10.1126/sciadv.add4201 (2023).

    Google Scholar 

  37. Rubin, E. B. et al. Molecular and phylogenetic analyses reveal mammalian-like clockwork in the honey bee (Apis mellifera) and shed new light on the molecular evolution of the circadian clock. Genome Res. 16, 1352–1365. https://doi.org/10.1101/gr.5094806 (2006).

    Google Scholar 

  38. Ma, D. et al. A transcriptomic taxonomy of Drosophila circadian neurons around the clock. eLife 10, e63056. https://doi.org/10.7554/eLife.63056 (2021).

  39. Barber, A. F., Fong, S. Y., Kolesnik, A., Fetchko, M. & Sehgal, A. Drosophila clock cells use multiple mechanisms to transmit time-of-day signals in the brain. Proc. Natl. Acad. Sci. U.S.A. 118, e2019826118. https://doi.org/10.1073/pnas.2019826118 (2021).

  40. Naeger, N. L. et al. Neurogenomic signatures of Spatiotemporal memories in time-trained forager honey bees. J. Exp. Biol. 214, 979–987. https://doi.org/10.1242/jeb.053421 (2011).

    Google Scholar 

  41. Moore, D., Siegfried, D., Wilson, R. & Rankin, M. A. The influence of time of day on the foraging behavior of the Honeybee, apis mellifera. J. Biol. Rhythms. 4, 305–325. https://doi.org/10.1177/074873048900400301 (1989).

    Google Scholar 

  42. Gronenberg, W. Subdivisions of hymenopteran mushroom body Calyces by their afferent supply. J. Comp. Neurol. 435, 474–489. https://doi.org/10.1002/cne.1045 (2001).

    Google Scholar 

  43. Heinze, S. & Homberg, U. Maplike representation of celestial E -Vector orientations in the brain of an insect. Science 315, 995–997. https://doi.org/10.1126/science.1135531 (2007).

    Google Scholar 

  44. Brockmann, A. & Robinson, G. E. Central projections of sensory systems involved in honey bee dance Language communication. Brain Behav. Evol. 70, 125–136. https://doi.org/10.1159/000102974 (2007).

    Google Scholar 

  45. Hensgen, R., England, L., Homberg, U. & Pfeiffer, K. Neuroarchitecture of the central complex in the brain of the honeybee: neuronal cell types. J. Comp. Neurol. 529, 159–186. https://doi.org/10.1002/cne.24941 (2021).

    Google Scholar 

  46. Fuchikawa, T. et al. Neuronal circadian clock protein oscillations are similar in behaviourally rhythmic forager honeybees and in arrhythmic nurses. Open. Biol. 7, 170047. https://doi.org/10.1098/rsob.170047 (2017).

    Google Scholar 

  47. Seeley, T. D. The Wisdom of the Hive: the Social Physiology of Honey Bee Colonies (Harvard Univ. Press), 1995).

  48. Reinhard, J., Srinivasan, M. V. & Zhang, S. Scent-triggered navigation in honeybees. Nature 427, 411–411. https://doi.org/10.1038/427411a (2004).

    Google Scholar 

  49. Herrero, A. et al. Coupling neuropeptide levels to structural plasticity in drosophila clock neurons. Curr. Biol. 30, 3154–3166e4. https://doi.org/10.1016/j.cub.2020.06.009 (2020).

    Google Scholar 

  50. Frisch, B. & Aschoff, J. Circadian rhythms in honeybees: entrainment by feeding cycles. Physiol. Entomol. 12, 41–49. https://doi.org/10.1111/j.1365-3032.1987.tb00722.x (1987).

    Google Scholar 

  51. Jain, R. & Brockmann, A. Time-restricted foraging under natural light/dark condition shifts the molecular clock in the honey bee, Apis mellifera. Chronobiol. Int. 35, 1723–1734. https://doi.org/10.1080/07420528.2018.1509867 (2018).

    Google Scholar 

  52. Machado Almeida, P., Lago Solis, B., Stickley, L., Feidler, A. & Nagoshi, E. Neurofibromin 1 in mushroom body neurons mediates circadian wake drive through activating cAMP–PKA signaling. Nat. Commun. 12, 5758. https://doi.org/10.1038/s41467-021-26031-2 (2021).

    Google Scholar 

  53. Hasegawa, S. et al. Hippocampal clock regulates memory retrieval via dopamine and PKA-induced GluA1 phosphorylation. Nat. Commun. 10, 5766. https://doi.org/10.1038/s41467-019-13554-y (2019).

    Google Scholar 

  54. Lehmann, M., Gustav, D. & Galizia, C. G. The early bee catches the flower – circadian rhythmicity influences learning performance in honey bees, apis mellifera. Behav. Ecol. Sociobiol. 65, 205–215. https://doi.org/10.1007/s00265-010-1026-9 (2011).

    Google Scholar 

  55. Shieh, K. R. Distribution of the rhythm-related genes rPERIOD1, rPERIOD2, and rCLOCK, in the rat brain. Neuroscience 118, 831–843. https://doi.org/10.1016/S0306-4522(03)00004-6 (2003).

    Google Scholar 

  56. Houl, J. H., Yu, W., Dudek, S. M. & Hardin, P. E. Drosophila CLOCK is constitutively expressed in circadian oscillator and Non-Oscillator cells. J. Biol. Rhythms. 21, 93–103. https://doi.org/10.1177/0748730405283697 (2006).

    Google Scholar 

  57. Smies, C. W., Bodinayake, K. K. & Kwapis, J. L. Time to learn: the role of the molecular circadian clock in learning and memory. Neurobiol. Learn. Mem. 193, 107651. https://doi.org/10.1016/j.nlm.2022.107651 (2022).

    Google Scholar 

  58. Gerstner, J. R. & Yin, J. C. P. Circadian rhythms and memory formation. Nat. Rev. Neurosci. 11, 577–588. https://doi.org/10.1038/nrn2881 (2010).

    Google Scholar 

  59. Lehr, A. B., McDonald, R. J., Thorpe, C. M., Tetzlaff, C. & Deibel, S. H. A local circadian clock for memory? Neurosci. Biobehav. Rev.. 127, 946–957. https://doi.org/10.1016/j.neubiorev.2020.11.032 (2021).

    Google Scholar 

  60. Homberg, U. In search of the Sky compass in the insect brain. Naturwissenschaften 91, 199–208. https://doi.org/10.1007/s00114-004-0525-9 (2004).

    Google Scholar 

  61. Zhu, H. et al. Cryptochromes define a novel circadian clock mechanism in monarch butterflies that May underlie sun compass navigation. PLoS Biol. 6, e4. https://doi.org/10.1371/journal.pbio.0060004 (2008).

    Google Scholar 

  62. Wahl, O. Beitrag Zur Frage der biologischen bedeutung des Zeitgedächtnisses der Bienen. Z. F Vergl Physiologie. 18, 709–717. https://doi.org/10.1007/BF00338365 (1933).

    Google Scholar 

  63. Farris, S. M. Evolution of complex higher brain centers and behaviors: behavioral correlates of mushroom body elaboration in insects. Brain Behav. Evol. 82, 9–18. https://doi.org/10.1159/000352057 (2013).

    Google Scholar 

  64. Couto, A. et al. Rapid expansion and visual specialisation of learning and memory centres in the brains of Heliconiini butterflies. Nat. Commun. 14, 4024. https://doi.org/10.1038/s41467-023-39618-8 (2023).

    Google Scholar 

  65. Buehlmann, C. et al. Mushroom bodies are required for learned visual Navigation, but not for innate visual Behavior, in ants. Curr. Biol. 30, 3438–3443e2. https://doi.org/10.1016/j.cub.2020.07.013 (2020).

    Google Scholar 

  66. Moore, D. & Doherty, P. Acquisition of a time-memory in forager honey bees. J. Comp. Physiol. A. 195, 741–751. https://doi.org/10.1007/s00359-009-0450-7 (2009).

    Google Scholar 

  67. Eban-Rothschild, A. D. & Bloch, G. Differences in the sleep architecture of forager and young honeybees(Apis mellifera). J. Exp. Biol. 211, 2408–2416. https://doi.org/10.1242/jeb.016915 (2008).

    Google Scholar 

  68. Wheeler, M. M., Ament, S. A., Rodriguez-Zas, S. L., Southey, B. & Robinson, G. E. Diet and endocrine effects on behavioral maturation-related gene expression in the Pars intercerebralis of the honey bee brain. J. Exp. Biol. Jeb. 119420. https://doi.org/10.1242/jeb.119420 (2015).

  69. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 30, 2114–2120. https://doi.org/10.1093/bioinformatics/btu170 (2014).

    Google Scholar 

  70. Andrews, S. FastQC: A quality control tool for high throughput sequence data. Online. (2010).

  71. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21. https://doi.org/10.1093/bioinformatics/bts635 (2013).

    Google Scholar 

  72. Liao, Y., Smyth, G. K. & Shi, W. FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930. https://doi.org/10.1093/bioinformatics/btt656 (2014).

    Google Scholar 

  73. Love, M. I., Huber, W. & Anders, S. Moderated Estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https://doi.org/10.1186/s13059-014-0550-8 (2014).

    Google Scholar 

  74. Wu, G., Anafi, R. C., Hughes, M. E., Kornacker, K. & Hogenesch, J. B. MetaCycle: an integrated R package to evaluate periodicity in large scale data. Bioinformatics 32, 3351–3353. https://doi.org/10.1093/bioinformatics/btw405 (2016).

    Google Scholar 

  75. Ge, S. X., Jung, D. & Yao, R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics 36, 2628–2629. https://doi.org/10.1093/bioinformatics/btz931 (2020).

    Google Scholar 

  76. Poulopoulos, A. et al. Subcellular transcriptomes and proteomes of developing axon projections in the cerebral cortex. Nature 565, 356–360. https://doi.org/10.1038/s41586-018-0847-y (2019).

    Google Scholar 

  77. Pharris, M. C. et al. An automated workflow for quantifying RNA transcripts in individual cells in large data-sets. MethodsX 4, 279–288. https://doi.org/10.1016/j.mex.2017.08.002 (2017).

    Google Scholar 

  78. Moore, D. Honey bee circadian clocks: behavioral control from individual workers to whole-colony rhythms. J. Insect. Physiol. 47, 843–857. https://doi.org/10.1016/S0022-1910(01)00057-9 (2001).

    Google Scholar 

  79. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods. 9, 676–682. https://doi.org/10.1038/nmeth.2019 (2012).

    Google Scholar 

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Acknowledgements

We thank Gene E. Robinson, Wulfila Gronenberg, and Charlotte Helfrich-Förster for their comments on an earlier version of the manuscript. We also thank the Next Generation Genomics Facility at NCBS, particularly Awadhesh Pandit for assisting with the RNA-seq run. We are grateful to the Central Imaging and Flow Cytometry Facility (CIFF) and the instrumentation team at NCBS for their support. We acknowledge the technical advice and support from Zeiss Microscopy team and Advanced Cell Diagnostics (ACD). Further, we thank Dimple Notani and Sheeba Vasu for their advice and Abhishek Bhattacharya for support in maintaining access to experimental facilities. We are thankful to Lukumoni Das, Sukrithi N Venu and Sripriya Bulusu for helping with the behavioral experiments.

Funding

Open access funding provided by Department of Atomic Energy. This study was supported by funding to TR (TIFR graduate student fellowship), NCBS-TIFR institutional funds to AB (No. P4167 and N1158) and the Department of Atomic Energy, Government of India (No. 12-R&D-TFR-5.04–0800 and 12-R&D-TFR-5.04–0900).

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Authors and Affiliations

  1. National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, 560065, India

    Tiyasa Roy & Axel Brockmann

  2. Aix-Marseille Université – CNRS UMR 7283, Institut de Microbiologie de la Méditerranée and Turing Center for Living Systems, Marseille, France

    Rikesh Jain

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  1. Tiyasa Roy
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  2. Rikesh Jain
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Contributions

Conceptualization: T.R., A.B.; Methodology: T.R., A.B.; Investigation: T.R.; Visualization: T.R., R.J., A.B.; Formal analysis: T.R., R.J., A.B.; Funding acquisition: A.B.; Supervision: A.B.; Writing-original draft: T.R., A.B.; Writing-review and editing: T.R., A.B.

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Tiyasa Roy or Axel Brockmann.

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Roy, T., Jain, R. & Brockmann, A. Transcriptional responses in feeder time-trained foragers suggest diverse interactions between the circadian clock and mushroom bodies in honey bees.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-31775-8

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  • DOI: https://doi.org/10.1038/s41598-025-31775-8

Keywords

  • Time-memory
  • Circadian clock
  • Mushroom bodies
  • Kenyon cells
  • Central complex
  • Time-series RNA sequencing
  • RNAscope labeling
  • Honey bees

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