Disease model organism for Parkinson disease: Drosophila melanogaster
Open accessAbstract
Parkinson's disease (PD) is a common neurodegenerative disorder characterized by selective and progressive loss of dopaminergic neurons. Genetic and environmental risk factors are associated with this disease. The genetic factors are composed of approximately 20 genes, such as SNCA, parkin, PTEN-induced kinase1 (pink1), leucine-rich repeat kinase 2 (LRRK2), ATP13A2, MAPT, VPS35, and DJ-1, whereas the environmental factors consist of oxidative stress-induced toxins such as 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP), rotenone, and paraquat. The analyses of their functions and mechanisms have provided important insights into the disease process, which has demonstrated that these factors cause oxidative damage and mitochondrial dysfunction. The most invaluable studies have been performed using disease model organisms, such as mice, fruit flies, and worms. Among them, Drosophila melanogaster has emerged as an excellent model organism to study both environmental and genetic factors and provide insights to the pathways relevant for PD pathogenesis, facilitating development of therapeutic strategies. In this review, we have focused on the fly model organism to summarize recent progress, including pathogenesis, neuroprotective compounds, and newer approaches. [BMB Reports 2019; 52(4): 250-258].
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In Drosophila melanogaster under hypergravity conditions, there is a significant reduction of dopaminergic neurons compared with the control group, in a similar way to human Parkinson's disease.
“Another study that used Drosophila melanogaster showed a significant reduction of dopaminergic neurons, compared with the control group, under hypergravity conditions in a similar way to human’s Parkinson’s disease (PD)98.”
From Key points for the development of antioxidant cocktails to prevent cellular stress and damage caused by reactive oxygen species (ROS) during manned space missions (2021) · cites this paper as [98]
The Introduction and the section on dopaminergic neurons describe neuronal loss in Drosophila models of Parkinson’s disease. The paper does not report a hypergravity experiment, a control-group comparison, or a statistically significant reduction under those conditions; it is a review, not the study described. (LLM, conf=0.84)
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Advancement in the animal model-based therapeutics in neurodegenerative diseases
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Idowu, O. K., Oremosu, A. A., & Dosumu, O. O. (2026) · Metabolic Brain Disease · doi:10.1007/s11011-026-01795-y · Cited by 1 · see citing works
Baisgaard, A. E., Koldby, K. M., Kristensen, T., Nyegaard, M., & Rohde, P. D. (2023) · Insects · doi:10.3390/insects14020168 · Cited by 1 · see citing works
Absence of pretaporter restrains features of the parkin phenotype in Drosophila
Silvera, M. C., Cantera, R., & Ferreiro, M. J. (2024) · Experimental Neurology · doi:10.1016/j.expneurol.2024.114997 · Cited by 1 · see citing works
Thane, M., Paisios, E., Stöter, T., Krüger, A.-R., Gläß, S., Dahse, A.-K., Scholz, N., Gerber, B., Lehmann, D. J., & Schleyer, M. H. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.27.509663 · Cited by 1 · see citing works
Sanz, F., Solana‐Manrique, C., & Paricio, N. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.28.522104 · Cited by 1 · see citing works
Exhaustive benchmarking of de novo assembly methods for eukaryotic genomesPreprint
Southwood, D., Rane, R., Lee, S. F., Oakeshott, J. G., & Ranganathan, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.18.537422 · Cited by 1 · see citing works
Rai, J., Aswini, S., Paul, S., Shelke, T., & Gupta, I. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.04.647141 · Cited by 1 · see citing works
Modeling Mechanisms and Applications of Parkinson's Disease Animal ModelsPreprint
Cui, Y., LIANG, Y., Liu, Y., & Zhang, B. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4175871
A genome-scale metabolic model of Drosophila melanogaster for integrative analysis of brain diseasesPreprint
Cesur, M. F., Patil, K. R., & Çakır, T. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.22.504778
Circadian clock disruption promotes the degeneration of dopaminergic neuronsPreprint
Dorcikova, M. M., Duret, L. C., Pottié, E., & Nagoshi, E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.15.512376
Usefulness of Drosophila in studying Parkinson's disease and role of natural plant products
(2023) · Advances in neurotoxicology · doi:10.1016/bs.ant.2023.01.007
Dhande, S. R., & Pansare, N. (2024) · Research Journal of Pharmacy and Technology · doi:10.52711/0974-360x.2024.00491
Maintenance of Mitochondrial Dynamics for Healthy Brain Ageing
Mishra, E., & Thakur, M. K. (2024) · Healthy ageing and longevity · doi:10.1007/978-3-031-68513-2_10
Modeling of Parkinson's Disease in Different Models
Subhan, I., & Siddique, Y. H. (2024) · CNS & Neurological Disorders - Drug Targets · doi:10.2174/0118715273326866240922193029
Ethical regulations for induction and validation of PD models
Oraby, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-16128-5.00019-0
Sayed, F. E., Mahmoud, A. K., Mohammed, O. A. M., Soliman, R. I., & Abdur-Rahman, M. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-16128-5.00014-1
Neuroprotective role of ranolazine in Parkinson disease: Drosophila melanogaster model
Parvesh, P., Kumar, S., Singh, G., Khatri, R., Shkula, S., Kaushik, K., Lather, A., & Hooda, T. (2025) · Scripta Medica · doi:10.5937/scriptamed56-53259
AGAKWU, M. U., OGUNMEFUN, G. S., YUSUF, H. O., ONMONYA, Y. A., & ADUNBI, J. O. (2024) · Journal of Biochemistry and molecular biology · doi:10.36108/jbmb/4202.20.0140
Anadu, V. E., Jimoh-Abdulghaffaar, H. O., Gilbert, T. T., Aneke, O. V., Arietarhire, L. O., Ichipi-Ifukor, P. C., Abdullahi, A. M., Okah, L., Sabine, A. F. Y., Oritsetimeyin, B. U., et al. (2025) · Biology Open · doi:10.1242/bio.061998
- Authors
- Aryal, B., & Lee, Y.
- Affiliations
- Kookmin University (KR)
- Venue
- BMB Reports
- Published
- 2019-04-30
- Volume
- 52
- Issue
- 4
- Pages
- 250-258
- ISSN
- 1976-6696 (ISSN-L)
- 1976-670X
- PMC
- PMC6507844
- OpenAlex
- W2942930317
- Cited by
- 111
- References
- 100
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 21 · 2023: 25 · 2022: 20 · 2021: 9 · 2020: 7 · 2019: 5
- FWCI
- 6.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- BMB Reports (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Research Foundation of Korea (NRF-2016R1D1A1B03931273, NRF-2018R1A2B6004202)
- Ministry of Education
- Kookmin University
- Topics
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Nuclear Receptors and Signaling
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Keywords
- Parkinson's disease, Drosophila melanogaster, dopaminergic neuron loss, neurodegeneration, genetic risk factors, environmental risk factors, oxidative stress, mitochondrial dysfunction, neuroprotective compounds, Parkin, LRRK2, MPTP, rotenone, paraquat, SNCA, PINK1, DJ-1, ATP13A2, MAPT, VPS35
- MeSH terms
- Leucine-Rich Repeat Serine-Threonine Protein Kinase-2, Protein Deglycase DJ-1, PTEN-Induced Putative Kinase, Adenosine Triphosphatases, Animals, Disease Models, Animal, Drosophila melanogaster, Humans, Membrane Proteins, Mitochondria, Parkinson Disease, Hazardous Substances, Protein Serine-Threonine Kinases, Oxidative Stress, Neurodegenerative Diseases, Drosophila Proteins, Vesicular Transport Proteins, Ubiquitin-Protein Ligases, alpha-Synuclein, Dopaminergic Neurons
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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