Boy fly meets girl fly meets AI: Training an AI to recognize mating flies identifies a gene for mating locations

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image: Boy fly meets girl fly meets AI: Training an AI to recognize mating flies identifies a gene for mating locations.
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Credit: Hayato M. Yamanouchi, Nagoya University

A research team at the Nagoya University Graduate School of Science in Japan has used artificial intelligence to determine that the Piezo, a channel that receives mechanical stimuli, plays a role in controlling the mating posture of male fruit flies (Drosophila melanogaster). Piezo inhibition led the flies to adopt an ineffective mating posture which reduced their reproductive performance. Their findings have been reported in iScience.

Most previous animal mating studies have been limited to behavioral studies, limiting our understanding of this essential process. Since many animals adopt a fixed posture when mating, maintaining an effective mating position is vital to reproductive success. In fruit flies, the male mounts the female and maintains this posture at least until she transfers enough sperm to fertilize the female, which occurs about 8 minutes after copulation begins. The Nagoya University research team realized that certain factors were involved in maintaining this copulation posture.

A likely contender is Piezo. Piezo is a family of transmembrane proteins found in bristle cells, the sensitive cells in the male genitalia. The piezo is activated when a mechanical force is applied to a cell membrane, allowing ions to flow through the channel and generate an electrical signal. This signal triggers cellular responses, including the release of neurotransmitters in neurons and the contraction of muscle cells. Such feedback helps a fly maintain its mating position.

After identifying that the piezo gene is involved in fruit fly mating, Professor Azusa Kamikouchi (s/he), assistant professor Ryoya Tanaka (he/he) and student Hayato M. Yamanouchi (he/he) have used optogenetics to further explore the neural mechanism of this phenomenon. This technique combines genetic engineering and optical science to create genetically modified neurons that can be inactivated with light of specific wavelengths. When the light was turned on during the pairing, the neuron was silenced. This allowed the researchers to manipulate the activity of piezo-expressing neurons.

“This step proved to be a big challenge for us,” said Kamikouchi. “Using optogenetics, specific neurons are silenced only when exposed to photostimulation. However, our interest was in silencing neural activity during copulation. Therefore, we had to make sure that the light was only on during pairing. However, if the experimenter manually triggered photostimulation in response to the animal’s copulation, he had to observe the animal during the experiment. Waiting for fruit flies to mate is incredibly time-consuming.”

The observation problem led the team to establish an experimental deep learning system that could recognize copulation. By training the AI ​​to recognize when intercourse occurred, they could automatically control photostimulation. This allowed them to discover that when piezo-expressing neurons were inhibited, males adopted a wobbly and largely ineffective mating posture. As one might expect, males who showed difficulty adopting an appropriate sex position had fewer offspring. They concluded that a key role of the piezo gene was helping the male shift her axis in response to the female for maximum mating success.

“Piezoelectric proteins have been implicated in a variety of physiological processes, including tactile sensation, hearing, blood pressure regulation and bladder function,” Kamikouchi said. “Now our results suggest that Replay can be added to the list. Because mating is an important reproductive behavior that is largely conserved in animals, understanding its control mechanism will lead to greater understanding of the reproductive system of animals in general.”

Kamikouchi is enthusiastic about the use of artificial intelligence in this research. ‘With the recent development of computer science, experimental systems and methods of analysis have advanced considerably,’ he concludes. “In this research, we succeeded in creating a device that automatically detects mating using real-time analysis based on machine learning and controls the photostimulation needed for optogenetics. To study the neural mechanisms that control animal behavior, it is important to conduct experiments in which neural activity is manipulated only when an individual exhibits a specific behavior. The method established in this study can be applied not only to studying mating in fruit flies but also to various behaviors in other animals. It should make a significant contribution to the promotion of neurobiological research.”


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