Scientists use AI-designed serotonin sensor to watch sleep, mental heath: Study

Washington: Researchers have described how they used advanced gene-splicing techniques to rework a bacterial protein into a replacement research tool which will help monitor serotonin transmission with greater fidelity than current methods.

In a piece of writing in Cell, National Institutes of Health-funded researchers described how they used advanced gene-splicing techniques to rework a bacterial protein into a replacement research tool which will help monitor serotonin transmission with greater fidelity than current methods. Preclinical experiments, primarily in mice, showed that the sensor could detect subtle, real-time changes in brain serotonin levels during sleep, fear, and social interactions, also as test the effectiveness of latest psychoactive drugs.

The study was funded, in part, by the NIH`s Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative which aims to revolutionize our understanding of the brain under healthy and disease conditions.

The study was led by researchers within the lab of Lin Tian, Ph.D., PI at the University Of California Davis School of drugs . Current methods can only detect broad changes in serotonin signaling. during this study, the researchers transformed a nutrient-grabbing, Venus flytrap-shaped bacterial protein into a sensitive sensor that fluorescently lights up when it captures serotonin.

Previously, scientists within the lab of Loren L. Looger, Ph.D., Hughes Medical Institute Janelia Research Campus, Ashburn, Virginia, used traditional gene-splicing techniques to convert the bacterial protein into a sensor of the neurotransmitter acetylcholine. The protein, called OpuBC, normally snags the nutrient choline, which features a similar shape to acetylcholine.

For this study, the Tian lab worked with Dr. Looger`s team and therefore the lab of Viviana Gradinaru, Ph.D., Caltech, Pasadena, California, to point out that they needed the added help of AI to completely redesign OpuBC as a serotonin catcher.

The researchers used machine learning algorithms to assist a computer `think up` 250,000 new designs. After three rounds of testing, the scientists settled on one. Initial experiments suggested that the new sensor reliably detected serotonin at different levels within the brain while having little or no reaction to other neurotransmitters or similarly shaped drugs. Experiments in mouse brain slices showed that the sensor skilled serotonin signals sent between neurons at synaptic communications points.

Meanwhile, experiments on cells in Petri dishes suggested that the sensor could effectively monitor changes in these signals caused by drugs, including cocaine, MDMA (also referred to as ecstasy), and a number of other commonly used antidepressants.

Finally, experiments in mice showed that the sensor could help scientists study serotonin neurotransmission under more natural conditions. as an example , the researchers witnessed an expected rise in serotonin levels when mice were awake and a fall as mice fell asleep. They also spotted a greater drop when the mice eventually entered the deeper, R.E.M. sleep states.

Traditional serotonin monitoring methods would have missed these changes. additionally , the scientists saw serotonin levels rise differently in two separate brain fear circuits when mice were warned of a foot shock by a ringing bell. In one circuit — the medial prefrontal cortex — the bell triggered serotonin levels to rise fast and high whereas within the other — the basolateral amygdala — the transmitter crept up to slightly lower levels. within the spirit of the BRAIN Initiative, the researchers decide to make the sensor readily available to other scientists.

They hope that it’ll help researchers gain a far better understanding of the critical role serotonin plays in our daily lives and in many psychiatric conditions.