FB2026_03 , released September 17, 2026
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Citation
Yang, D.M., Manurung, R.V., Lin, Y.S., Chiu, T.Y., Lai, W.Q., Chang, Y.F., Fu, T.F. (2020). Monitoring the Heavy Metal Lead Inside Living Drosophila with a FRET-Based Biosensor.  Sensors (Basel) 20(6): E1712.
FlyBase ID
FBrf0245245
Publication Type
Research paper
Abstract
The harmful impact of the heavy metal lead on human health has been known for years. However, materials that contain lead remain in the environment. Measuring the blood lead level (BLL) is the only way to officially evaluate the degree of exposure to lead. The so-called "safe value" of the BLL seems to unreliably represent the secure threshold for children. In general, lead's underlying toxicological mechanism remains unclear and needs to be elucidated. Therefore, we developed a novel genetically encoded fluorescence resonance energy transfer (FRET)-based lead biosensor, Met-lead, and applied it to transgenic Drosophila to perform further investigations. We combined Met-lead with the UAS-GAL4 system to the sensor protein specifically expressed within certain regions of fly brains. Using a suitable imaging platform, including a fast epifluorescent or confocal laser-scanning/two-photon microscope with high resolution, we recorded the changes in lead content inside fly brains ex vivo and in vivo and at different life stages. The blood-brain barrier was found to play an important role in the protection of neurons in the brain against damage due to the heavy metal lead, either through food or microinjection into the abdomen. Met-lead has the potential to be a powerful tool for the sensing of lead within living organisms by employing either a fast epi-FRET microscope or high-resolution brain imaging.
PubMed ID
PubMed Central ID
PMC7146181 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Sensors (Basel)
    Title
    Sensors (Basel, Switzerland)
    ISBN/ISSN
    1424-8220
    Data From Reference
    Alleles (5)
    Chemicals (1)
    Genes (2)
    Human Disease Models (1)
    Insertions (1)
    Transgenic Constructs (4)