Using a Combination of Novel Research Tools to Understand Social Interaction in the Drosophila melanogaster Model for Fragile X Syndrome.
Maja StojkovicMilan PetrovicMaria CapovillaSara MilojevicVedrana MakevicDejan B BudimirovicLouise CorscaddenShuhan HeDragana D ProticPublished in: Biology (2024)
Fragile X syndrome (FXS), the most common monogenic cause of inherited intellectual disability and autism spectrum disorder, is caused by a full mutation (>200 CGG repeats) in the Fragile X Messenger Ribonucleoprotein 1 ( FMR1 ) gene. Individuals with FXS experience various challenges related to social interaction (SI). Animal models, such as the Drosophila melanogaster model for FXS where the only ortholog of human FMR1 ( dFMR1 ) is mutated, have played a crucial role in the understanding of FXS. The aim of this study was to investigate SI in the dFMR1 B55 mutants (the groups of flies of both sexes simultaneously) using the novel Drosophila Shallow Chamber and a Python data processing pipeline based on social network analysis (SNA). In comparison with wild-type flies ( w 1118 ), SNA analysis in dFMR1 B55 mutants revealed hypoactivity, fewer connections in their networks, longer interaction duration, a lower ability to transmit information efficiently, fewer alternative pathways for information transmission, a higher variability in the number of interactions they achieved, and flies tended to stay near the boundaries of the testing chamber. These observed alterations indicate the presence of characteristic strain-dependent social networks in dFMR1 B55 flies, commonly referred to as the group phenotype. Finally, combining novel research tools is a valuable method for SI research in fruit flies.
Keyphrases
- drosophila melanogaster
- wild type
- intellectual disability
- autism spectrum disorder
- healthcare
- mental health
- network analysis
- endothelial cells
- attention deficit hyperactivity disorder
- genome wide
- health information
- case report
- machine learning
- dna methylation
- big data
- artificial intelligence
- deep learning
- induced pluripotent stem cells