A serotonin sensor designed by AI can help scientists study sleep and mental health

In an article in Cell, researchers funded by the National Institutes of Health described how they used advanced genetic engineering to convert a bacterial protein into a new research tool that could monitor serotonin transmission more accurately than current methods.

Preclinical experiments, mainly on mice, showed that the sensor could detect subtle changes in serotonin levels in the brain during sleep, anxiety, and social interactions in real time and test the effectiveness of new psychiatric drugs.

The study was funded in part by NIH Brain Research through the Initiative to Promote Innovative Neurotechnology (BRAIN), which aims to revolutionize our understanding of the brain in healthy and disease-related conditions.

The study was led by researchers in the laboratory of Lin Tian, ​​PhD, principal researcher at the University of California Davis School of Medicine. Current methods can only detect broad changes in serotonin signaling. In this study, the researchers converted a nutrient-rich bacterial protein in the form of a Venus flytrap into a highly sensitive sensor that lights up fluorescent when serotonin is captured.

Previously, scientists in the laboratory of Loren L. Looger, PhD, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, used traditional genetic engineering techniques to convert the bacterial protein into a sensor for the neurotransmitter acetylcholine.

The protein, called OpuBC, usually captures the nutrient choline, which is similar in form to acetylcholine. For this study, the Tian laboratory worked with Dr. Looger and the lab of Viviana Gradinaru, Ph.D., Caltech, Pasadena, Calif., Worked together to show that they needed the extra help from artificial intelligence to completely redesign OpuBC as a serotonin scavenger.

The researchers used machine learning algorithms to help a computer “invent” 250,000 new designs. After three rounds of testing, the scientists decided on one. Initial experiments indicated that the new sensor reliably detects serotonin at different levels in the brain, while it hardly or not at all reacts to other neurotransmitters or similarly shaped drugs.

Experiments in mouse brain slices showed that the sensor responded to serotonin signals sent between neurons at synaptic communication points. Meanwhile, experiments on cells in Petri dishes suggested that the sensor can effectively monitor changes in these signals caused by drugs such as cocaine, MDMA (also known as ecstasy), and several commonly used antidepressants.

Finally, experiments in mice showed that the sensor could help scientists study serotonin neurotransmission in more natural conditions. For example, the researchers observed an expected increase in serotonin levels when mice were awake and a decrease when mice fell asleep.

They also discovered a larger drop off as the mice eventually entered deeper REM sleep states. Traditional serotonin monitoring methods would have missed these changes. In addition, the scientists saw that serotonin levels rose differently in two separate brain anxiety circuits when mice were warned of foot shock by a ringing bell.

In one circuit – the medial prefrontal cortex – the bell triggered a rapid and high rise in serotonin levels, while in the other – the basolateral amygdala – the transmitter rose to slightly lower values.

In the spirit of the BRAIN initiative, the researchers plan to make the sensor available to other scientists. They hope this will help researchers better understand the crucial role serotonin plays in our daily lives and in many psychiatric conditions.

.

Source link : https://gadgets.ndtv.com/science/news/ai-artificial-intelligence-serotonin-sensor-national-institutes-of-health-nih-sleep-mental-health-brain-2343464#rss-gadgets-all