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New AI system can decode fruit fly behaviors: Why that matters for future human genetic research

New AI system can decode fruit fly behaviors: Why that matters for future human genetic research

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Fly Drosophila sp. Credit: Muhammad Mahdi Karim / Wikipedia. GNU Free Documentation License, Version 1.2

How do you know if a fruit fly is hungry? Ask a computer.

While that sounds like a bad dad joke, it’s reality at Tulane University, where researchers have developed a new AI tool that can tell you if a fruit fly is hungry, sleepy or singing (yes , fruit flies sing).

Dubbed MAFDA (for Novel Machine-learning-based Automatic Fly-behavioral Detection and Annotation) the system uses cameras and a newly developed software to track and identify the complex interactive behaviors of individual flies over more big group This allows researchers to compare and contrast the behaviors of fruit flies with different genetic backgrounds.

For more than a century, scientists have used fruit flies’ simple genomes and short lifespans to unravel the mysteries of inheritance and survival in humans in studies of Drosophila melanogaster that have earned six Nobel Prizes Prize. Fruit flies and humans share 60% of the same DNA.

Previous algorithms were less accurate at tracking individual flies within a group, but the MAFDA system makes studying small insects much easier.

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“Fruit flies are like pioneers in discovering new things, from the chromosome theory of inheritance to innate immunity,” said corresponding author Wu-Min Deng, Ph.D. , professor of biochemistry and molecular biology and the Gerald & Flora Jo Mansfield Piltz Endowed Professor of Cancer Research at Tulane School of Medicine. “To be able to quantify the behavior of flies is really a step forward in the study of behavior.”

Wenkan Liu, a School of Medicine graduate student who developed the MAFDA system, said the importance of the platform is “undeniable.”

“It speeds up research, minimizes human error, and provides intricate insights into the genetics of behavior,” Liu said. “This tool is potentially important because it improves reproducibility and paves the way for new explorations in large-scale behavioral analysis.”

MAFDA was developed as part of a recent study, which discovered that the gene that causes flies to detect pheromones is the same gene that controls pheromone production. These findings, published in Advances in Sciencechallenge the status quo view that separate genes control pheromone production and perception and have broad applications in the fields of human behavioral evolution, metabolism and sex dimorphism.

Going forward, researchers hope to see MAFDA used in a variety of applications. Jie Sun, lead author and postdoctoral fellow at Tulane School of Medicine, said MAFDA could eventually be used to study other insects as well as mice and fish, and the system is can be useful in studying the effects of drugs.

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“The more information we give the machine, the better it gets at correctly identifying different behaviors from courtship to feeding and so on,” Sun said. “It’s a very important, meaningful tool.”

MAFDA is already used in other research projects at Tulane, and researchers are working to package the system so that it can be used by more scientists at Tulane and around the world .

“That’s the goal,” Deng said. “The original idea was to determine the health status of the flies. It might be too much to ask at the moment, but we hope it will be more widely available to the community and hopefully in the future we can get into that direction.”

Additional information:
Jie Sun et al, Integration of lipid metabolism, pheromone production and perception of Fruitless and Hepatocyte nuclear factor 4, Advances in Science (2023). DOI: 10.1126/sciadv.adf6254. www.science.org/doi/10.1126/sciadv.adf6254

Journal information:
Advances in Science

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