Metabolism: Insulin control in fruit flies

Investigating how the production of insulin is regulated in fruit flies reveals surprising insights that may help to better understand how this process unfolds in humans.
  1. Omowumi Kayode  Is a corresponding author
  1. Department of Biochemistry, Mountain Top University, Nigeria

In humans, the pancreas plays a crucial role in regulating blood sugar levels by producing a hormone called insulin. In fruit flies, cells in the brain called insulin-producing cells (IPCs for short) perform a similar function. These tiny insects may seem like an unlikely choice for studying insulin regulation, but their biology shares many similarities with humans. By studying fruit flies, scientists can gain valuable insights into complex biological processes, including metabolism, insulin production and diseases like diabetes (Marder, 2012; Taghert and Nitabach, 2012).

Whether in insects or mammals, maintaining stable blood sugar levels requires insulin release to be carefully regulated (Meyer et al., 2021). In fruit flies, chemicals called neuromodulators ‘tell’ IPCs when and how to produce the hormone. This involves small protein-like molecules (known as neuropeptides), as well as biogenic amines such as dopamine and serotonin, binding to receptors on the surface of the cells. Each type of neuromodulator can increase or decrease insulin release, depending on what the body needs (Taghert and Nitabach, 2012). Yet, precisely how neuromodulators interact with IPCs in fruit flies is still poorly understood; in particular, it remains unclear whether these cells exhibit functional diversity – that is, whether individual IPCs respond to various neuromodulatory signals in different ways. Now, in eLife, Jan Ache and colleagues – including first authors Martina Held, Rituja Bisen and Meet Zandawala – report a comprehensive analysis of how IPCs are controlled in fruit flies (Held et al., 2025).

The team, who are based at Julius-Maximilians-University of Würzburg, the University of Nevada Reno and Charité–Universitätmedizin Berlin, used a variety of techniques to manipulate and monitor brain signals in the insects. This allowed them to observe how both individual cells and populations of IPCs responded to various neuromodulators.

The experiments revealed that certain signals could influence the overall activity of the cells. Quick-acting biogenic amines like octopamine and dopamine, for example, made IPCs release more insulin. These chemicals control energy use: dopamine is linked to motivating and reward, while octopamine shapes the response to stress and excitement, much like adrenaline in humans. As such, these signals likely help the body prepare for activity by ensuring enough resources are available. On the other hand, long-acting neuropeptides like leucokinin and myosuppressin reduced IPC activity and slowed insulin release. This may help conserve energy when food is scarce or during stress (Rosikon et al., 2023).

At the level of individual cells, the work by Held et al. confirmed that IPCs have heterogeneous roles in balancing metabolism, with some cells reacting strongly to certain neuromodulators while others remained unresponsive. This is similar to how human pancreatic beta cells behave, with various cells responding differently to various signals (Meyer et al., 2021). This diversity may help fine-tune insulin release, preventing sudden changes in blood sugar levels (Bisen et al., 2024; Held et al., 2025).

Taken together, these findings will enable further research into insulin regulation in fruit flies, which may hold the key to unlocking long-sought answers in how this process unfolds in humans. For instance, further studies could focus on exploring how the different signals controlling insulin release work together. Do some of them override others? And how do long-term changes, like obesity or diabetes, affect these signals? Answering these questions could lead to better treatments for metabolic diseases, such as diabetes.

References

    1. Meyer D
    2. Richter F
    3. Schmitt H
    (2021)
    Cellular diversity in pancreatic beta cells: implications for insulin secretion
    Metabolic Biology 18:150–165.

Article and author information

Author details

  1. Omowumi Kayode

    Omowumi Kayode is in the Department of Biochemistry, Mountain Top University, Makogi Oba, Nigeria

    For correspondence
    otkayode@mtu.edu.ng
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5831-3558

Publication history

  1. Version of Record published:

Copyright

© 2025, Kayode

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 315
    views
  • 39
    downloads
  • 0
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Omowumi Kayode
(2025)
Metabolism: Insulin control in fruit flies
eLife 14:e106220.
https://doi.org/10.7554/eLife.106220
  1. Further reading

Further reading

    1. Neuroscience
    Guoling Tang, Yaning Han ... Pengfei Wei
    Tools and Resources

    Deep learning-based methods have advanced animal pose estimation, enhancing accuracy, and efficiency in quantifying animal behavior. However, these methods frequently experience tracking drift, where noise-induced jumps in body point estimates compromise reliability. Here, we present the anti-drift pose tracker (ADPT), a transformer-based tool that mitigates tracking drift in behavioral analysis. Extensive experiments across cross-species datasets—including proprietary mouse and monkey recordings and public Drosophila and macaque datasets—demonstrate that ADPT significantly reduces drift and surpasses existing models like DeepLabCut and SLEAP in accuracy. Moreover, ADPT achieved 93.16% identification accuracy for 10 unmarked mice and 90.36% accuracy for freely interacting unmarked mice, which can be further refined to 99.72%, enhancing both anti-drift performance and pose estimation accuracy in social interactions. With its end-to-end design, ADPT is computationally efficient and suitable for real-time analysis, offering a robust solution for reproducible animal behavior studies. The ADPT code is available at https://github.com/tangguoling/ADPT.

    1. Neuroscience
    Andrea Sattin, Chiara Nardin ... Tommaso Fellin
    Research Advance

    Two-photon (2P) fluorescence imaging through gradient index (GRIN) lens-based endoscopes is fundamental to investigate the functional properties of neural populations in deep brain circuits. However, GRIN lenses have intrinsic optical aberrations, which severely degrade their imaging performance. GRIN aberrations decrease the signal-to-noise ratio (SNR) and spatial resolution of fluorescence signals, especially in lateral portions of the field-of-view (FOV), leading to restricted FOV and smaller number of recorded neurons. This is especially relevant for GRIN lenses of several millimeters in length, which are needed to reach the deeper regions of the rodent brain. We have previously demonstrated a novel method to enlarge the FOV and improve the spatial resolution of 2P microendoscopes based on GRIN lenses of length <4.1 mm (Antonini et al., 2020). However, previously developed microendoscopes were too short to reach the most ventral regions of the mouse brain. In this study, we combined optical simulations with fabrication of aspherical polymer microlenses through three-dimensional (3D) microprinting to correct for optical aberrations in long (length >6 mm) GRIN lens-based microendoscopes (diameter, 500 µm). Long corrected microendoscopes had improved spatial resolution, enabling imaging in significantly enlarged FOVs. Moreover, using synthetic calcium data we showed that aberration correction enabled detection of cells with higher SNR of fluorescent signals and decreased cross-contamination between neurons. Finally, we applied long corrected microendoscopes to perform large-scale and high-precision recordings of calcium signals in populations of neurons in the olfactory cortex, a brain region laying approximately 5 mm from the brain surface, of awake head-fixed mice. Long corrected microendoscopes are powerful new tools enabling population imaging with unprecedented large FOV and high spatial resolution in the most ventral regions of the mouse brain.